Alexander Luria

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thesis.
EVALUATING THE IMPACT OF ATTENTION PROCESS TRAINING
(APT) ON ATTENTION DEFICIT IN THE EARLY STAGES OF
RECOVERY FROM STROKE
A thesis submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy
in
Psychology
at
The University of Waikato
by
Margaret Diana Dudley
2011
ii
Abstract
Attention deficits are a prominent sequel of stroke and impact negatively
on rehabilitation outcomes. However, rehabilitation efforts are almost entirely
concerned with the remediation of physical impairments that result from the
stroke despite the involvement of attention in physical functioning. Attention
Process Training (APT) is a cognitive retraining programme originally designed
for the remediation of attention deficit following traumatic brain injury.
However, the efficacy of APT post-stroke is not yet known, as to date, few studies
have been conducted with small sample sizes. This study evaluated the
effectiveness of APT in improving attention in stroke survivors within the five to
eight week period post-stroke. Seventy eight patients admitted to hospital with
first-ever-stroke were identified as having an attention deficit by obtaining a score
of one standard deviation below the normative mean on any of the following
widely-used neuropsychological measures of attention; the Auditory Attention
Quotient (AAQ) or Visual Attention Quotient (VAQ) of the Integrated Visual and
Auditory Continuous Performance Test, (IVA-CPT), either trial of the Trail
Making Test (TMT), the Paced Auditory Serial Addition Test (PASAT), or by
three or more errors made on the left or right side of the Bells Cancellation Test.
These measures were re-administered on completion of treatment. Participants
were randomised to either the experimental group who received standard care and
up to 30 hours of APT or to a control group that received standard care only. The
primary outcome measure was the Full Scale Attention Quotient (FSAQ) of the
IVA-CPT which is a measure of attention derived from both auditory and visual
attention quotients. The secondary outcome measure was a health-related quality
iii
of life measure, the SF-36, (Short-Form-36). Both measures were administered
before treatment and again on the completion of treatment. The results showed
that on the primary outcome, the APT group showed improvement from baseline
to post-treatment whereas the SC group had not. Significant improvement by the
APT group was also demonstrated on two other measures of the IVA-CPT
including the Auditory Attention Quotient and the Full Scale Response Quotient
(a measure of impulsivity). On the quality of life measure neither the APT group
nor the SC group demonstrated a significant change in scores.
The results of this study provide further support for the efficacy of cognitive
rehabilitation and in particular that APT is an effective cognitive treatment option
for the remediation of attention deficit in the early stages of stroke recovery. The
characteristics of stroke survivors who might benefit most from APT are
identified as well as those factors that possibly influence the subjective experience
of this particular intervention. The appropriateness of some measures such as the
PASAT, the TMT, cancellation tests as well as continuous performance tests that
are often used in research of attention deficit, are also discussed in the context of a
stroke population.
It is hopeful that the optimistic outcomes of this study will encourage
further needed research in this area in order to inform stroke rehabilitation
specialists to incorporate cognitive rehabilitation into predominantly physicallyfocussed programmes.
iv
Maraea Dudley
1923-2005
You raised your eight children and worked full time throughout. You were the
hardest working person I have known. I am so proud of you. This is for you mum.
I wish you were here to enjoy it with me.
v
Acknowledgements
Ko Te Rarawa raaua, Te Aupouri, Ngati Kahu nga iwi
Ko Orowhana te Maunga
Ko Manukau te marae
Ko Whakamaharatanga te whare tupuna
Ko Norman Henry Dudley toku papa
Ko Maraea Karaka toku mama
The writing of this PhD has been an adventure and in the main I have thoroughly
enjoyed the journey. There have been a number of people who have helped me
along the way and without them I would never have reached my destination.
First and foremost my gratitude is extended to those stroke patients of
Middlemore and North Shore Hospitals who so generously gave of themselves to
participate in this study, particularly at such a distressing time in their lives. Also,
the medical, administrative and allied health staff of both hospitals who were so
accommodating to the research team. It was a privilege to work amongst you all.
I have been so fortunate to have had two supervisors of such high calibre to
inform and guide me. Meetings with my primary supervisor Dr Nicola Starkey
always filled me with inspiration. Learning so much from Nicola was the exciting
part of this experience. Dr Suzanne Barker-Collo provided the opportunity for me
to work on the START project which led to me writing this thesis and for that I
vi
am so thankful. The feedback from both my supervisors was always speedy and
detailed and kept me on track and focussed.
I would like to acknowledge The Health Research Council of New Zealand for
awarding me the Clinical Research Training Fellowship that allowed me to work
on this project on a full time basis and complete it within a relatively short time.
At my stage of life, time is of the essence! The fellowship also afforded me the
opportunity to present this study to the 7th World Stroke Conference in Seoul,
South Korea, in October 2010. I also acknowledge and thank the Maori
Education Foundation and the Ministry of Health for their assistance.
To Professor Janet Leathem and Professor Linda Smith, I am so very grateful to
you both for your support and encouragement over the years. I am privileged to
have had the guidance of two such esteemed people.
I wish to acknowledge the Maori and Indigenous programme (MAI) ki TamakiMakaurau and MAI ki Waikato arms of Nga Pae o Te Maramatanga. This
programme provides support to Maori students undertaking doctoral studies. The
time spent with this group was so valuable particularly the writing retreats which
provided a stimulating environment that fired the neurons into writing mode.
Sharon Rickard and Lee Daniels of Te Aho Tapu Trust Psychological Services
have been a constant source of support to me and I wish to pay tribute to their
kaupapa that provides a unique Maori-focussed service to the people of South
Auckland.
vii
My fellow researcher on this project was Sylvia Hach who has also become a
close and dear friend. It was a privilege to work with Sylvie whose standard of
research was par excellence. To my dear friend Trish Nazzari, I can‟t thank you
enough for your generosity and the emotional support you have given me over the
years, particularly while I have been writing up this thesis. Meeting for those
countless cups of coffee gave me much needed respite and renewed motivation to
continue with the seemingly endless task of writing. The many phone calls made
to Erana Cooper particularly towards the end of the journey usually led to lots of
laughter and a lifting of anxiety. Tena koe e hoa. Ka aroha nui ki a koe.
I am grateful to Angela Rudland from the Community Based Rehabilitation Team
at Middlemore Hospital, for helping me out with word processing skills.
I want to acknowledge my sister Norma for her encouragement and support. Also,
my whanau from Manukau ki Te Tai Tokerau for your kind wishes of
encouragement particularly in the closing stages of this journey. Kia ora koutou.
Ka aroha nui ki a koutou.
Finally, to my daughter Rachael, thank you for helping me with the tedious task of
checking all those references. But mostly, thank you for your loyalty and constant
love – you know it is mutual.
viii
Table of Contents
Abstract.......................................................................................................................
Acknowledgements.....................................................................................................
Table of Contents........................................................................................................
List of Tables...............................................................................................................
List of Figures..............................................................................................................
List of Abbreviations...................................................................................................
ii
v
viii
xi
xii
xiii
Chapter 1: Stroke..........................................................................................................
1.1
Description of Stroke............................................................................
1.2
Epidemiology of Stroke........................................................................
1.3
Economics of Stroke.............................................................................
1.4
Mortality...............................................................................................
1.5
Risk Factors..........................................................................................
1.6
Prevention of Stroke.............................................................................
1.7
After-effects of Stroke..........................................................................
1
3
7
9
11
11
13
14
Chapter 2: Outcomes of Stroke....................................................................................
2.1
Overview of Physical Medical and Psychological Outcomes..............
2.2
Cognitive Difficulties...........................................................................
2.3
Specific Cognitive Domains.................................................................
2.4
Memory................................................................................................
2.5
Executive Functions.............................................................................
2.6
Attention Deficit..................................................................................
2.7
Theories of Attention...........................................................................
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15
16
20
20
21
24
27
Chapter 3: Cognitive Rehabilitation............................................................................
3.1
Approaches to Cognitive Rehabilitation..............................................
3.1.1 Restorative Therapy..................................................................
3.1.2 Compensatory Therapy............................................................
3.1.3 Environmental Therapy............................................................
3.1.4 Behaviour Therapy...................................................................
3.2
Efficacy of Cognitive Rehabilitation...................................................
3.3
Cognitive Rehabilitation following Stroke..........................................
3.4
Evidence for Rehabilitation of Attention.............................................
3.5
Barriers to Trials in Cognitive Rehabilitation......................................
3.6
Appropriateness of Control Conditions................................................
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Methods.......................................................................................................................
4.1
Ethics....................................................................................................
4.2
Participants...........................................................................................
4.2
Design..................................................................................................
4.2.1 Study Overview.........................................................................
4.3
Apparatus and Measures......................................................................
4.3.1 Eligibility Measures..................................................................
4.3.1.1 MMSE...........................................................................
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77
ix
4.3.2 Baseline Measures....................................................................
4.3.2.1 Barthel Index................................................................
4.3.3 Neuropsychological Measures.................................................
4.3.4 Attention...................................................................................
4.3.3.1 IVA-CPT......................................................................
4.3.3.2 Paced Auditory Serial Addition Test...........................
4.3.3.4 Trail Making Test Part A & B......................................
4.3.3.2 The Bells Cancellation Test.........................................
4.3.5 Other Neuropsychological Baseline Measures........................
4.3.4.1
Executive Functions.........................................
4.3.4.1.1
The Stroop Test.........................
4.3.4.2
Memory............................................................
4.3.4.2.1
CVLT........................................
4.3.4.2.2
Logical Memory........................
4.3.4.2.3
Visual Paired Associates..........
4.3.4.2.4
ROCF........................................
4.3.4.3
Language..........................................................
4.3.4.3.1
Boston Naming Test..................
4.3.4.3.2
COWA......................................
4.3.5 Health Related Quality of Life Measures.................................
4.3.5.1
SF-36................................................................
4.3.5.2
modified Rankin Scale.....................................
4.3.5.3
Cognitive Failures Questionnaire.....................
4.3.5.4
General Health Questionnaire..........................
Primary Outcome Measure...................................................................
Secondary Outcome Measure...............................................................
Intervention – Attention Process Training...........................................
4.6.1 Sustained Attention Tasks.........................................................
4.6.1.1
Auditory Tasks.................................................
4.6.1.2
Visual Tasks.....................................................
4.6.2 Selective Attention Tasks..........................................................
4.6.2.1
Auditory Tasks.................................................
4.6.2.2
Visual Tasks.....................................................
4.6.3 Alternating Attention Tasks......................................................
4.6.3.1
Flexible Number and Shape Cancellation........
4.6.3.2
Odd and even number identification................
4.6.3.2
Addition/Subtraction Flexibility......................
4.6.3.3
Set Dependent Activities 1...............................
4.6.3.4
Set Dependent Activities 11.............................
4.6.4 Divided Attention Tasks............................................................
4.6.4.1
Auditory Tasks.................................................
4.6.4.2
Visual Tasks.....................................................
Design Overview
Procedure.............................................................................................
4.7.2 Therapy Regime.......................................................................
78
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Results........................................................................................................................
5.1
Part 1: Analyses of Baseline Measures................................................
5.2
Part 2: Analyses of Primary and Secondary Outcome Measures.........
5.3
Part 3: Analyses of Qualitative Data....................................................
119
120
133
136
4.4
4.5
4.6
4.7
4.7
x
5.4
5.3.1 Changes in qualitative ranges from pre to post-intervention.... 142
Part 4: Factors influencing progress through APT............................... 150
Discussion..............................................................................................................
6.1
Main Findings......................................................................................
6.2
Similarities with previous studies........................................................
6.3
Differences from previous studies........................................................
6.4
Health Related Quality of Life results..................................................
6.5
Changes as an effect of time................................................................
6.6
Appropriateness of measures...............................................................
6.7
Factors that may have influenced outcomes........................................
6.8
Factors that may have influenced how the participants engaged in
APT......................................................................................................
6.9
Which patients might benefit most from APT? ..................................
6.10 Attention abilities of stroke survivors in the early stages of recovery.
6.11 Limitations...........................................................................................
6.12 Implications of this study....................................................................
6.13 Conclusions..........................................................................................
6.14 Future Research....................................................................................
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169
References............................................................................................................
186
Appendix A
Appendix B
Appendix C
Appendix D
Appendix E
237
253
275
279
Appendix F
Stroke Risk Factors..........................................................................
Outcomes of Stroke..........................................................................
Participant Information Sheet..........................................................
Consent Form...................................................................................
Tables showing correlations between baseline and postintervention measures with the highest tasks reached on APT........
Tables showing correlations between baseline and postintervention measures with total hours of APT completed..............
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284
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List of Tables
Table
Table
Table
Table
Table
Table
Table
1
2
3
4
5
6
7
Table
8
Table
9
Table
10
Table
11
Table
Table
Table
12
13
14
Table
15
Table
16
Table
17
Table
18
Table
Table
Table
19
20
21
Sohlberg and Mateer‟s Clinical Model of Attention.............
Studies evaluating scanning interventions for neglect..........
Studies evaluating general attention interventions................
Studies evaluating Attention Process Training......................
Schedule of Assessments.......................................................
Order in which APT exercises were administered................
Demographics of participants randomised to APT and SC
groups....................................................................................
Performance of the APT and SC groups on baseline
measures of attention and the SF-36.....................................
Performance of the APT and SC groups on baseline
neuropsychological measures of executive functions,
memory and language and remaining health related quality
of life measures......................................................................
Correlations of demographic and functional variables with
baseline measures of attention...............................................
Means and standard deviations of baseline attention
measures according to ethnicity type.....................................
Means and standard deviations of baseline attention
measures for stroke type........................................................
Correlations between baseline measures of attention
measures and other neuropsychological measures................
Descriptive and inferential statistics showing significant
results in bold........................................................................
Proportion of participants in each qualitative category on
measures of attention.............................................................
Proportion of participants in each qualitative category on
measures of executive functioning, language and memory...
Changes across qualitative categories by the APT group
from baseline to post-intervention. Data presented as
percent of participants who fell within each category at
baseline and post-intervention...............................................
Changes across qualitative categories by the SC group
from baseline to post-intervention. Data presented as
percent of participants...........................................................
Means and standard deviations of change in categories
from baseline to post-intervention for both APT and SC
groups....................................................................................
Means and standard deviations of ethnicity and stroke type
for total highest auditory and visual task reached.................
Means and standard deviations for ethnicity and stroke type
for the mean number of hours of APT completed.................
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109
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135
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150
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List of Figures
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
1
2
Early Selection Theory of Attention..............................................
Modified Early Selection Theory of Attention (Treisman‟s
Attenuator Theory).........................................................................
3 Late Selection Theory of Attention................................................
4 Baddeley‟s Model of Attention......................................................
5 Flow chart showing each stage of study.........................................
6 Number of hours completed by each participant............................
7 Highest task achieved by each participant.....................................
8 The effects of APT on IVA-CPT measures....................................
9 Bar graph showing the category changes from baseline to posttreatment for the main findings for both the APT and Standard
Care Groups...................................................................................
10 Comparison of the categories moved from pre to post-treatment
for all scores of the IVA-CPT for both APT and Standard Care
groups............................................................................................
11 Comparison of the categories moved from pre to post-treatment
for scores of the TMT Part A & B and PASAT 2.4 and 2.0 trials
for both APT and Standard Care groups........................................
12 Comparison of the categories moved from pre to post-treatment
for scores on the Bells Cancellation Test for both APT and
Standard Care groups.....................................................................
29
29
30
31
75
118
118
136
145
147
148
149
xiii
List of Abbreviations
AAN
AAQ
ACRM
ADLs
AHA
ANCOVA
ANOVA
APT
APQ
BASIS
BDI
BI
BIAA
BNT
CCT
CFQ
CHI
COAST
COWA
CPSP
CPT
CRP
CTT
CVA
CVLT
DALYs
EBIQ
ED
EFNS
fMRI
FSAQ
FSRQ
HRQoL
IVA-CPT
LACS
LM
MCI
MCS
MMSE
MOANS
mRS
NIHSS
NINDS
NINDS-CSN
OHI
OT
PACS
American Academy of Neurology
Auditory Attention Quotient
American Congress of Rehabilitation Medicine
Activities of Daily Living
American Heart Association
Analysis of co-variance
Analysis of variance
Attention Process Training
Auditory Prudence Quotient
Boston Acute Stroke Imaging Scale
Beck Depression Inventory
Barthel Index
Brain Injury Association of America
Boston Naming Test
Clinical Control Trial
Cognitive Failures Questionnaire
Closed Head Injury
California Older Adult Stroop Test
Controlled Oral Word Association
Central Post Stroke Pain
Continuance Performance Test
Cognitive Remediation Programme
Consonant Trigrams
Cerebrovascular Accident
California Verbal Learning Test
Disability Adjusted Life Years
European Brain Injury Questionnaire
Executive Dysfunction
European Federation of Neurological Societies
Functional Magnetic Resonant Imaging
Full Scale Attention Quotient
Full Scale Response Quotient
Health Related Quality of Life
Integrated Visual & Auditory Continuous Performance Test
Lacunar Stroke
Logical Memory
Mild Cognitive Impairment
Mental Component Summary
Mini Mental State Exam
Mayo‟s Older Americans Normative Studies
modified Rankin Scale
National Institute of Health Stroke Scale
National Institute of Neurological Disorders and Stroke
National Institute of Neurological Disorders and Stroke-Canadian
Stroke Network
Open Head Injury
Occupational Therapy
Partial Anterior Circulation Stroke
xiv
PASAT
PCS
PFO
PICH
POCS
PSHVF
RCI
RCT
ROCF
SAH
SD
SF-36
SIS
SSD
START
TACS
TBI
TEA
TLC-E
tPA
TIA
UI
VAQ
VPA
VPQ
WAIS
WAIS-R
WISC 111
WHO
WMS
Paced Auditory Serial Addition Test
Physical Component Summary
Patent Foramen Ovale
Primary Intracerebral Haemorrhage
Posterior Circulation Stroke
Post-stroke Homonymous Visual Field
Reliable Change Index
Randomised Control Trial
Rey-Osterrieth Complex Figure
Subarachnoid Haemorrhage
Standard Deviation
Short Form Questionnaire-36
Stroke Impact Scale
Single Subject Design
Stroke Attention Rehabilitation Trial
Total Anterior Circulation Stroke
Traumatic Brain Injury
Test of Everyday Attention
Test of Language Competence-Expanded Version
Tissue Plasminogen Activator
Transient Ischaemic Attack
Urinary Incontinence
Visual Attention Quotient
Visual Paired Associates
Visual Prudence Quotient
Wechsler Adult Intelligence Scale
Wechsler Adult Intelligence Scale-Revised
Wechsler Intelligence Scale for Children-Third Edition
World Health Organisation
Wechsler Memory Scale
1
“Suffering isn’t ennobling, recovery is”
Christiaan Barnard
Chapter 1: Stroke
Stroke is the most common disabling neurological condition of adults
world-wide with survivors experiencing physical impairments, personality
changes, disruption of family and community living, and decreases in vocational
functioning (Anderson, 1992). Traditionally, rehabilitation from stroke has
focused on recovery of physical abilities and speech/language rehabilitation
(Paolucci et al., 1996). However, survivors of stroke commonly present with
cognitive impairment that can create lifelong burdens for the individuals and their
caregivers. Despite this common problem, relatively little research has been
conducted into the efficacy of cognitive rehabilitation following stroke. Without
this knowledge base the perception that cognitive retraining is ineffective and
unrelated to physical recovery, continues to propagate. Indeed, even those
patients who are aware of their cognitive deficits are more likely to focus their
energy on physical rehabilitation with the expectation of achieving quicker and
more observable outcomes, leaving little reserve for other rehabilitation pathways.
In the last few decades major forces that have helped fuel the advancement
of cognitive rehabilitation have included, the exponential growth in new
technology, new perspectives and findings with regard to neuro-plasticity,
cutbacks in the health care sector, an increasing sense of self-empowerment
regarding health issues, and a growing emphasis on functional outcomes of
rehabilitation. Cognitive rehabilitation has become increasingly recognised as a
method designed to reduce cognitive dysfunction and assist individuals in
compensating for its impact on daily living (Wilson, 1997). Systematic reviews
2
of cognitive rehabilitation that have been conducted in the United States
(Cicerone et al., 2000; 2005; Sohlberg et al., 2003) along with research conducted
in Europe (Lincoln, Majid, & Weyman, 2000; Majid, Lincoln & Weyman, 2000)
have added to a growing bank of evidence for the efficacy of cognitive
rehabilitation (Halligan & Wade, 2005; High, Sander, Struchen, & Hart, 2005).
In response to this now substantial bank of evidence, the Brain Injury
Association of America (BIAA) in 2009 urged the American government to
include under the military healthcare insurance scheme, full access to cognitive
rehabilitation for its military personnel who had suffered a traumatic brain injury.
The BIAA stated that cognitive therapy is “one of the most widely accepted and
critical rehabilitative treatments” for traumatic brain injury (BIAA, 2006).
The purpose of my thesis was to evaluate the efficacy of an attention
rehabilitation programme in stroke survivors with attention deficit which has been
found to be a common area of cognitive impairment following stroke
(Hochstenbach, Mulder, van Limbeek, Donders, & Schoonderwaldt, 1998; Nys,
2005; Tuhrim, 1993). Attention is a particularly important aspect of cognitive
functioning as it is reported to be the basis for other areas of cognition including
memory, communication, and executive functioning (Bennett, 1998; Whyte,
1992).
In order to place this study within its appropriate context, this review of the
literature will begin with providing a definition of stroke followed by a
presentation of the various taxologies of the disease. A summary of the
epidemiology of the disease including the burden of stroke will then be presented
followed by a summary of the risk factors associated with the disease. The
subsequent chapter will then identify the after-effects of stroke leading to an
3
overview of the possible cognitive deficits that may result from this condition. A
discussion on cognitive rehabilitation will then provide the background for a
closer examination of attention deficit as a cognitive impairment following stroke,
with an analysis of the interventions that have been utilised to date. Finally, there
will be a discussion of the challenges often confronted when conducting research
of behavioural interventions followed by a number of suggestions that will
hopefully help researchers overcome those challenges.
Description of Stroke
The terms stroke and cerebrovascular accident (CVA) are used
interchangeably to describe brain damage or dysfunction that occurs as a result of
some disruption in the vascular supply to or of the brain. The term stroke,
however, conveys the suddenness and randomness with which it occurs and has
now become the preferred term of use (Lindley, 2008). Stroke is a heterogenous
term incorporating a set of neurological symptoms that lead to damage to the
brain and less commonly to the spinal cord (Caplan, 2000; Spengos et al., 2006).
The World Health Organisation‟s (WHO) broad definition of a stroke as “rapidly
developing clinical signs of focal (or global) disturbance of cerebral function, with
symptoms lasting 24 hours or longer or leading to death with no apparent cause
other than of vascular origin”, has sound practical application because of its nonreliance on imaging data and can therefore be used in countries where such
technology is not readily available (Kwan, 2001).
Stroke comes in two major forms and is generally categorised as either
ischaemic or haemorrhagic depending on the physiological antecedent (Lezak,
2005). An ischaemic stroke is the result of an interruption of the oxygen and
nutrient carrying blood supply to the brain.
4
After a few minutes without that supply brain cells begin to die. Ischaemic
strokes are more common accounting for approximately 80% of all strokes with
haemorrhagic strokes accounting for the remainder. The different causes and
location of the interruption of blood supply to the brain provides the basis for
subtypes of ischaemic stroke including, thrombosis, embolism, and systemic
hypoperfusion (Caplan, 2006; Rudd, Irwin, & Penhale, 2005). Strokes of an
undetermined cause constitute 30-40% of all ischaemic strokes and are termed
“cryptogenic” (Adams et al., 1993; Donnan, Fisher, MacLeod, & Davis, 2008).
A thrombotic stroke is formed within the brain itself and often arises due to
a localised occlusive process anywhere in the vascular system causing stenosis (an
abnormal narrowing in a blood vessel) or blockage in the larger arteries that
supply the brain, such as the carotid artery or the middle cerebral artery (Appel &
Linas, 2007). Atherosclerosis (the thickening of an artery wall as the result of a
build-up of fatty materials) is the most common disease that narrows the blood
flow in the artery and is most common where arteries branch or bifurcate
(Ponsford, 2004). This type of stroke is termed a large-vessel thrombosis while
small-vessel thrombosis involves one (or more) of the brain's smaller, yet deeper
penetrating arteries such as the anterior communicating artery or the posterior
communicating artery. This latter type of stroke is also called a lacunar stroke
(Donnan & Norrving, 2009; Hreib, 2008; Molina et al., 1999)
An embolic stroke, estimated to account for 15-20% of clinical stroke
events, is caused by a clot that is formed outside the brain and travels the
bloodstream until it becomes lodged and cannot travel any further. An embolic
stroke can itself be further divided into cardiac embolism where the clot arises
5
proximally most commonly from the heart, and artery-to-artery embolism where
the origins lie in major arteries and systemic veins (Bogousslavsky et al., 1991).
Systemic Hypoperfusion refers to the reduction in blood flow which can be
caused by bleeding, dehydration, or loss of fluid into body tissues (shock)
(Caplan, 1991). The permanent damage caused by such blockages is called an
infarct. Damage to the larger arteries which supply blood to important parts of the
brain such as those that control movement or speech can result in catastrophic
outcomes. Signs and symptoms commonly seen when having a stroke include
hemiparesis (weakness on one side of the body), aphasia (language disorder),
dysphagia (difficulty in swallowing), dysarthria (speech problems caused by the
muscles or nerves controlling them), hemianopia (visual field loss), ataxia (lack of
coordination of voluntary movement), apraxia (a disorder of the nervous system
which prevents the performance of tasks or movements despite having the
physical ability to do so) severe headache, and/or disturbed consciousness (WHO,
2005).
Various classification systems exist for acute ischemic stroke based on
factors such as clinical presentation and imaging as their distinguishing features.
Classification systems have been found to be important as they provide evidence
for determining prognosis, mortality rates and better management practices. For
example, The Boston Acute Stroke Imaging Scale (BASIS) is a system that has
been found to provide accurate prognostic data (Merino & Latour, 2008).
However, determining the subtype of Ischaemic stroke is often accomplished
using the criteria of TOAST (Trial of ORG 10172 in Acute Stroke Treatment), a
system based on clinical findings supported by brain, vascular and cardiac
imaging and includes the following five categories: (1) large-artery
6
atherosclerosis, (2) cardio-embolism, (3) small-artery occlusion, (4) stroke of
other determined aetiology, (5) stroke of undetermined aetiology (Adams et al.,
1993). The Oxford Community Stroke Project classification is another widely
used system based on the site and extent of the symptoms and the categories
include; Total Anterior Circulation Infarct (TACT), Partial Anterior Circulation
Infarct (PACT), Lacunar Infarct (LACI), and Posterior Circulation Infarct (POCI)
(Bamford, Dennis, Sandercock, Burn, & Warlow, 1990).
In a haemorrhagic stroke, as the name suggests, there is a leak or a bursting
of a blood vessel and the blood spills into areas of the brain usually from a
ruptured cerebral aneurysm or head injury, causing injury to the surrounding
areas. Haemorrhagic strokes which account for 10-20% of all strokes can be
further divided into categories; Primary Intracerebral Haemorrhage (PICH) and
Subarachnoid Haemorrhage (SAH). The two subtypes present with dissimilar
clinical problems and therefore necessitate different management methods. PICH
is the most frequent form of haemorrhagic stroke and occurs when a small artery
in the brain ruptures or leaks blood directly into the brain substance, often caused
by hypertension. A SAH on the other hand, describes the leakage of blood (from
aneurysms or arteriovenous malformations) onto the brain‟s surface which
circulates around the brain via the spinal fluid pathways (Caplan, 2000; Warlow et
al., 1996). SAH is a severe form of stroke with over 50% of patients dying in the
first three months and 10-15% dying before reaching hospital (van Gijn, Kerr, &
Rinkel, 2007).
A Transient Ischaemic Attack (TIA), although commonly referred to as a
“mini stroke” is a temporary reduction in blood supply resulting in disturbance in
body function lasting less than 24 hours and is therefore excluded from being
7
categorised as a stroke (Semple, 1998). However, TIA‟s have been shown to be
predictive of a more major stroke in the future (Coull, Lovett, & Rothwell, 2004;
Lovett et al., 2003).
Epidemiology of Stroke
Epidemiological studies of stroke present an enormous challenge given the
heterogeneity of the condition, a lack of readily available neuroimaging in
resource-poor regions, the absence of primary data from many countries and
differences in study design which make comparisons across populations difficult.
Malmgren et al. (1987) published a list of 12 methodological criteria to
standardise definitions and case ascertainment for the ideal study of stroke
incidence and/or mortality. These criteria have evolved over time and were later
updated by Bonita, Broad, Anderson and Beaglehole (1995), by Sudlow and
Warlow in 1996 by Feigin, Lawes, Bennett, and Anderson in 2003 and again by
Feigin and Vander Hoorn in 2004. In their population-based incident study of
stroke covering two decades Rothwell et al. (2004) employed new methodological
practises for the validation of completeness of case ascertainment for stroke.
Those practises included monthly investigations of data bases of general
practitioners in the study area to identify all patients coded with a cerebrovascular
diagnosis, with subsequent reviewing of all patients identified. Also, all patients
who were admitted to hospital with an acute vascular problem and all patients
undergoing elective or emergency coronary, carotid, or peripheral vascular
investigations or interventions, were reviewed on a daily basis. The utilisation of
these two methods resulted in an additional 16% of new stroke events in the
Rothwell study.
8
Based on these findings, Feigin and Vander Hoorn (2004) suggested that the
“ideal” criteria for a study of stroke incidence and/or mortality consists of three
categories including; Standard definitions, Standard methods, and Standard datapresentation. The WHO definition of stroke is recommended as the ideal criteria
and is the definition that has been widely used in incidence studies (Donnan, et
al., 2008; Feigin & Vander Hoorn, 2004). In addition to the WHO criteria, Feigin
& Vander Hoorn suggest at least 80% verification by neuroimaging for diagnosis
of ischaemic, intracerebral haemorrhage and subarachnoid haemorrhage,
classification of ischaemic stroke into subtypes, and separate and combined data
for first-ever-in-a-lifetime and recurrent stroke. Standardisation of methodological
practises include, a prospective study design with population-based case
ascertainment based on overlapping sources of information from hospital,
outpatient clinics, general practitioner data bases and death certificates, and a
large well-defined stable population with census data not more than 5 years old.
Standard data-presentation should cover complete calendar years and no more
than 5 years of data should be averaged together. Data on men and women should
be presented separately and age-specific estimates should be presented in middecade age bands (e.g. 45-54 years) that include the oldest age group (≥ 85 years)
and have 95% confidence intervals around rates.
The available data suggests that the human toll resulting from the increase
in the incident of stroke worldwide has reached pandemic proportions. In 2002,
the WHO released data identifying stroke as the cause of approximately 10% of
all deaths world-wide, ranking it as the second cause of death after ischaemic
heart disease, (excluding neoplastic diseases as a group; Dewey et al., 2004;
Feigin & Parag, 2007). In China, the most populous country on earth, stroke has
9
become the leading cause of death in many parts of the country (Xu, 2008).
Approximately 16 million first-ever strokes occur annually in the world. Recent
epidemiological studies report 85% of strokes now occur in low income and
middle income countries, despite these populations having a shorter life
expectancy (Feigin, Lawes, Bennett, Barker-Collo, & Parag, 2009; Johnson,
Mendis, & Mathers, 2009). In their systematic review of world-wide stroke
incidence spanning 28 countries, Feigin et al. (2009), provide data indicating that
high income countries have witnessed a 42% decrease in stroke in the last four
decades, however, in low to middle income countries over the same time period,
the incidence of stroke has increased by 100%. Their study showed that in the
years 2000 to 2008, stroke incidence rates in low to middle income countries for
the first time, exceeded the stroke incidence rates in high income countries and
has now reached epidemic proportions. Feigin et al. (2009) also found that over
the last four decades there was a greater reduction in the incidence of primary
intracerebral haemorrhage than of ischaemic stroke in high income countries
although the incidence of subarachnoid haemorrhage had not changed during the
same time period. Given that age is a major risk factor for stroke, more people are
at risk in a globally aging population (Dewey et al., 2004), and of those that
survive the stroke, between 15% and 30% are permanently disabled (Lloyd-Jones
et al., 2009) placing enormous social and economic burdens on national resources.
Economics of Stroke
The socioeconomic burden of stroke continues to escalate relative to a
worldwide aging population and an increased number of survivors of stroke. The
implications of this situation is no better illustrated than in Japan, a country that
enjoys a rapidly aging population but must now face the drastic economic
10
consequences of healthcare and in particular mounting pressure for more efficient
stroke rehabilitation (Liu, Chino, & Takahashi, 2000). A similar situation was
also revealed by Tobias, Cheung, Carter, Anderson, and Feigin (2007), in their
estimations and projections of stroke incidence, prevalence and mortality in New
Zealand where they found stroke mortality falling faster than stroke incidence.
While those results were representative of major public health achievements,
paradoxically, unless effective prevention, management and rehabilitation services
are developed accordingly, the burden of stroke will increase. Stroke remains the
leading cause of physical disability in adults over the age of 65 years and accounts
for one of the largest health burdens to face humanity. Stroke burden is projected
to rise from around 38 million disability-adjusted life years (DALYs) lost globally
in 1990 to 61 million DALYs in 2020 (MacKay & Mensah, 2004). In the United
States in 2008, the total direct costs of stroke (such as ambulance services,
hospitalisation, rehabilitation, nursing home costs, drugs and indirect costs like
lost wages) in those under 65 is estimated to be $65.5 billion and €38.1 billion in
European countries. In the United Kingdom (UK) total societal costs were
estimated at £8.9 billion which accounts for 5.5% of the total UK national health
expenditure (Dewey et al., 2004). Tobias et al. (2007), report a parallel situation in
New Zealand estimating a 4% reduction in stroke mortality between 1991 and
2003 against a 1% increase in stroke prevalence. Yet again, longer life
expectancy and new and improved strategies for acute stroke management in New
Zealand results in an increase in the number of stroke survivors thus placing everincreasing demands on health resources. The average lifetime cost of each stroke
in New Zealand for acute care, rehabilitation, support services, and institutional
care is estimated to be NZ$50,000 to NZ$100,000 (Gommans, 2004), with a total
11
quantifiable cost to the country estimated at up to $154 million per year
(Anderson et al., 2005, Payne, Huybrechts, Caro, Green, & Klittich, 2002; Scott &
Scott, 1994 ). The enormous drain stroke has on the annual health budget
highlights the urgency for better prevention and management strategies of this
health hazard.
Mortality
Recent studies investigating world-wide stroke mortality rates indicate
similar patterns of disparity to that found from incidence studies. For example,
Johnson et al. (2009) in their compilation and analysis of data from the WHO
Global Burden of Disease project (2002) found stroke mortality rates to be three
to five times higher in low-income countries than in middle to high income
countries. From a regional analysis they found national income to be a stronger
predictor of stroke burden and mortality than risk factors commonly used to assess
the cardiovascular health of a country such as diabetes, smoking, alcohol
consumption and high body-mass index. They proposed access to care and better
management of risk factors as reasons for the disparity. Epidemiological
transitional influences such as mortality, fertility, and migration are also
considered to be significant factors in the disparity between low and high income
countries (Carandang et al., 2006; Feigin et al., 2009; Johnson et al., 2009).
Risk Factors
Changes in the incidence and mortality rate for stroke are attributable to a
range of risk factors. The 1984 Framingham Study researching heart disease
coined the term “risk factor” (Wilson et al., 1998) to refer to those variables that
predicted an individual‟s likelihood of developing atherosclerosis or coronary
heart disease, the precursors of heart attacks. The term is now commonly used to
12
refer to any variable associated with an increased risk of disease or infection
although these are correlation and not necessarily causal relations. Upon followup, the Framingham Study found approximately 850 of the 5209 subjects included
in the study, subsequently suffered a stroke. This provided a unique opportunity
for the collection of a considerable data base on stroke risk factors. From this and
other epidemiological studies, it can also be deduced that stroke is largely a
preventable disease. Risk factors for stroke can be categorised into a dichotomy
of either modifiable (i.e., those that can be altered either by intervention), or not.
Non-modifiable risk factors include ageing, genetic predisposition, gender, low
birth weight and ethnicity (Humphries & Morgan, 2004), while modifiable factors
are mostly a combination of medical and behavioural causes. Medical risk factors
include hypertension, high levels of cholesterol, atherosclerosis (hardening of the
arteries), atrial fibrillation (irregular heartbeat), diabetes, sickle cell anaemia, and
migraine (Moskowitz & Kurth, 2007). Behaviours or lifestyle factors that
increase the risk of stroke include tobacco smoking (Feigin et al., 2005),
insufficient physical activity (Ellekjaer, Holmen, Ellekjaer, & Vatten, 2000),
alcohol abuse (Reynolds et al., 2003), unhealthy nutrition (Fisher, Lees & Spence,
2006) and obesity (Boden-Albala & Sacco, 2000; Walker et al., 1996). Other less
well-documented factors associated with stroke occurrence include low
socioeconomic status (Avendano et al., 2006; Cox, McKevitt, Rudd, & Wolfe,
2006; Wolfe et al, 2002), stress (Truelsen, Nielsen, Boysen, & Gronbaek, 2003),
infection (Lindsberg & Grau, 2003) , oral contraceptive use (Gillum, Mamidipudi,
& Johnston, 2000), pregnancy (Kitner et al., 1996), and lack of hormone
replacement therapy (Fieschi & Fisher, 2001; Li et al., 2008; Wolinsky et al.,
13
2009). A brief summary of the literature on modifiable and non-modifiable risk
factors is presented in Appendix A.
Prevention of Stroke
As the world's population ages, the collective risk of stroke increases so
there is a critical need for knowledge of intervention and prevention strategies in
order to reduce the rising prevalence of the disease. Awareness of epidemiology
and the consequences of stroke are vital in order to press governments, health
authorities, and patients into preventative action. Stroke is largely a preventable
disease and does not have to be a death sentence or even a life-changing illness.
In the United States, despite considerable public awareness campaigns,
knowledge of warning signs and risk factors remains abysmally poor, suggesting a
more proactive stance particularly within high risk populations is required
(Kleindorfer et al., 2009). Modifiable risk factors such as hypertension, diabetes,
atrial fibrillation, hyperlipidaemia, smoking, alcohol consumption, physical
inactivity and obesity are by far the worst contributors of stroke in developed
countries. Primary stroke prevention incorporating life style modifications to
reduce risk factors would have a substantial affect on reducing stroke incidence,
given that the American Heart Association identified 70% of strokes as being
first-ever events (AHA, 2003; Chiuve et al., 2008; Goldstein et al., 2009).
Patients with recurrent stroke have on average poorer outcomes than those with
first time strokes (Samsa, Bian, Lipscomb, & Matcher, 1999). Stroke survivors
have a 15-fold increased risk of stroke recurrence which is a consistent and
independent predictor not only of death but of disability, institutionalisation and a
decline into dependency (Burn et al., 1994; Hankey, Jamrozik, Broadhurst,
Forbes, & Anderson, 2002). The maintenance of a healthy life style, medication
14
therapies, surgical intervention, stenting and in-hospital management programmes
are all secondary stroke prevention techniques that have been found to reduce the
incidence of subsequent stroke events (Antiplatelet Trialists Collaboration, 1994,
1998; Biller et al., 1998).
After-effects of Stroke
Stroke fatality and stroke survival rates vary widely and are influenced by a
number of variables including type of stroke, severity of stroke, site of lesion,
expediency of medical intervention, comorbidity, previous health status, age,
socioeconomic status, time since stroke, and so forth. For those that survive the
stroke, the after-effects can be extensive, varying from person to person with
either physical, psychological or cognitive impairments or a combination of two
or all three dimensions.
In order to place this study in context, this chapter has provided a
background to the disease of stroke. The next chapter will begin with a brief
summary of the major physical, medical and psychological outcomes of stroke
thereby setting the framework for the introduction of cognitive deficits poststroke. The chapter will then lead to a discussion on attention deficit which is the
area of cognition that is the main focus of this study. Chapter three will begin
with an overview of the historical and current significance of cognitive
rehabilitation followed by a summary of the literature on attention deficit after
stroke and then the evidence for rehabilitation including Attention Process
Training (APT), will be summarised and analysed. Finally, a critique of research
conducted into cognitive rehabilitation will be conducted with some responses to
those problems identified in this area of research.
15
“There is no education like adversity”
Disraeli
Chapter 2: Outcomes of Stroke
Stroke is the most common disabling chronic condition which often results
in the loss of independence in a significant proportion of survivors. Furthermore,
the consequences of this disease can also have devastating effects on family and
friends, a high percentage of whom are required to make significant adjustments
to their lives in order to provide care for their loved ones with stroke (Anderson,
1992). Several scales have been developed to determine the neurological impact
of stroke such as the National Institutes of Health Stroke Scale (NIHSS; Schlegel
et al., 2003), the Canadian Neurological Scale (Cote, Hachinski, Shurvell, Norris,
& Wolfson, 1986) and the European Stroke Scale (Hanston et al., 1994). These
are often used in combination with health related quality of life (HRQoL) scales,
functional scales and outcome assessments to determine recovery and disability
after stroke.
Given that the focus of this study is concerning the field of cognition, only a
brief overview of the physical, medical and psychological outcomes of the disease
will be provided. There will however, be a greater focus on the cognitive
problems, in particular attention deficit, that may result from this syndrome. An
overview of the major theories of attention that have evolved will then be
discussed. More detailed information gathered as part of this study on physical,
medical and psychological outcomes of stroke are provided in Appendix B.
Overview of Physical Medical and Psychological Outcomes
The onset of a stroke often results in cognitive, physical, medical and
psychological impairment with devastating impact on aspects of daily life often
16
leading to a lack of social contact or social isolation. The identification of the
outcomes of stroke facilitates the management and treatment of the sequelae of
this disease and provides a rational basis for clinical guidelines that ultimately aim
to reduce the burden of stroke on the individual, his or her family and society. An
extensive range of classification systems for measuring stroke outcomes exist
including the National Institutes of Health Stroke Scale (HIHSS), the Stroke
Impact Scale (Duncan et al., 1999), the Barthel Index (Mahoney & Barthel, 1965),
the Functional Independence Measure (Hall et al., 1996), the Modified Rankin
Scale (Rankin, 1957), and the London Handicap Scale (WHO ICIDH, 1986) to
name some of the more commonly used measures. There are numerous other
measures specific to the various domains of impairment whether it is motor,
sensory, vision, language, cognition or affect (e.g., the Beck Depression Inventory
(Beck, Ward, Mendelson, Mock & Erbaugh, 1961). To provide some insight into
the difficulties stroke patients may suffer, the most common impairments that can
result from stroke are briefly described in Appendix B.
Cognitive Difficulties
Cognitive difficulties following stroke are present in as many as 50% to
65% of survivors (Ballard, et al., 2003; Bonita, Solomon, & Broad 1997;
Donovan et al., 2008; Hackett, Yapa, Parag, & Anderson, 2005; Hochstenbach et
al., 1998; Kase et al., 1998; Pohjasvaara et al., 1998; Rasquin et al., 2004; Saxena,
2006; Snaphapaan, Rijpkema, van Uden, Fernandez, & de Leeuw, 2009; Srikanth
et al., 2003), however, the real prevalence and natural course of post-stroke
cognitive disorders remains unclear as a result of difficulties comparing across
studies. Methodological features such as the heterogeneity of sample groups, the
inclusion or exclusion of subjects with recurrent strokes, the exclusion of younger
17
patients and those with aphasia, timing of assessment and selection of those
cognitive domains assessed, plus the use of different assessments, all contribute to
divergent and inconsistent data.
Hachinski and Bowler (1993) coined the term “vascular cognitive
impairment”, the use of which they suggested should include “the identification of
cognitive impairment, the recognition of a potential vascular cause, and the
establishment of a logical link between them”. It is a term which is commonly
used in contemporary literature and will therefore be used in this overview.
Vascular cognitive impairment is far from homogenous and varies according to
the location, number, size, and pathophysiology of the brain lesion (Greenberg,
2009; Nys, et al., 2005; Robinson et al., 1986). As Greenberg (2009, p. 214),
succinctly puts it “the effects of strokes on cognition likely represents the
cumulative effects of location, number, and volume”. Aminah, Normah, and
Ponnusamy (2008) speculate, however, that patients with right hemispheric
lesions are better able to cope than those patients with left hemispheric lesions
because speech and language functions are left intact and the patient is more able
to facilitate their recovery through verbal communication and positive self-talk.
There are other variables that have been found to influence vascular
cognitive impairment. For example, Saxena (2006) and Zhou et al. (2005) found
lesser education to be significantly correlated with higher vascular cognitive
impairment levels although in a more recent study, Aminah et al. (2008) failed to
find such an association. Increasing age has consistently been associated with
vascular cognitive impairment (Aminah et al., 2008; Downhill & Robinson, 1994;
Ebrahim, Nouri, & Barer, 1985; Saxena, 2006; Stephens et al. 2005; Tatemichi et
al., 1994). Indeed, increasing age was also found to correlate with the progression
18
of vascular cognitive impairment at 2 years post-stroke (del Ser et al., 2005).
Brodaty et al. (2005) also found a negative association between age and cognitive
decline.
Other factors that have been linked with increased risk of vascular cognitive
impairment include previous stroke (Mok et al., 2004; Zhou et al., 2005), prestroke cognitive decline (Mok et al., 2004; Wagle et al., 2009), high diastolic
blood pressure, number of prescribed drugs, hypotension and genetics (del Ser et
al., 2005; Wagle et al., 2009). Moyer (2004) found that stroke survivors who were
treated with statins for hypercholesterolemia prior to their stroke may be at less
risk of vascular cognitive impairment than other stroke survivors. However, to
date, research into vascular cognitive impairment is still in its infancy and
therefore the research available is somewhat exploratory and in need of further
verification.
Vascular cognitive impairment has also been shown to be a significant
predictor of outcomes of stroke (Barker-Collo & Feigin, 2006; Ebrahim et al.,
1985; McDowd, Filion, Pohl, Richards, & Stiers, 2003; Nurdan, Derya, Demet,
Betul, & Caglayan, 2010; Nys et al., 2005; Ozdemir, Birtane, Tabatabaei,
Ekukulu, & Kokino, 2001; Saxena, 2006) and quality of life (Mitchell, Kemp,
Benito-Leon, & Reuber, 2010). A study of hospital-based stroke patients at three
months found improved cognitive impairment, independent of physical
impairment, to be positively associated with independent living and functional
impairment (Tatemichi et al., 1994a). In a large cohort (n=486) of ischaemic
stroke patients, Pohjasvaara, Erkinjuntti, Vataja, and Kaste (1998) also found
cognitive decline to have an independent effect on dependence three months after
stroke.
19
Indeed, cognitive deficit in stroke patients has consistently been associated
with prolonged length of stay in hospital or rehabilitation settings (Galski, Bruno,
Zorowitz, & Walker, 1993; Saxena, Koh, Ng, Fong, & Yong, 2007) as long as
three years after the stroke (Pasquin, Leys, Rousseaux, Pasquier, & Henon, 2007).
Conversely, a study of Chinese stroke patients found that a shorter stay in hospital
was predicted by improved cognitive and self-care factors rather than mobility
factors (Man, Tam, & Hui-Chan, 2006).
Vascular cognitive impairment has also been found to have an impact on
the emotional state of the patient. Both depression and anxiety post-stroke have
consistently been associated with a higher incidence of cognitive impairment
(Kauhanen et al., 1999; Robinson et al., 1986; Saxena, 2006; Talelli et al., 2004)
and in particular with slowed cognitive speed and poorer verbal memory (BarkerCollo, 2007). However, the effects of vascular cognitive impairment have been
found to be even more far-reaching. For example, Patel, Coshall, Rudd, and
Wolfe, in their 2002 population-based study found cognitive impairment to be
significantly associated with death or disability at three and four years post-stroke.
In some instances the post-stroke cognitive impairments are progressive in
nature (Sachdev, Brodaty, Valenzuela, Lorentz, & Koschera, 2004), and reach the
level of dementia in 5-7% of patients during the first six months increasing to 2025% by five years. However, although post-stroke cognitive deficits can diminish
during the first year (Rasquin et al., 2004), it is not unusual for late spontaneous
and rehabilitative-related recovery (Cicerone et al., 2005; Moss & Nicholas,
2006).
20
Specific Cognitive Domains
The relationship between specific cognitive domains and outcomes after
stroke has also been investigated. The type of cognitive shifts demonstrated in
stroke patients include varying degrees of impairment of executive functioning ,
memory, visuospatial and visuoperceptual abilities, problem solving skills,
orientation, attention, rate of information processing, anosognosia, and agnosia,
singularly or a combination of two or more of these problems (Alladi, Meena, &
Kaul, 2002; Tatemichi et al., 1994a). With increasing recognition of the
importance of the role of cognitive function on treatment outcomes, the need for
ecologically valid cognitive measures is becoming an increasingly useful
requisite.
Memory
Memory impairment is a common cognitive deficit that occurs following
stroke. In a systematic review of the literature, Snaphaan and de Leeuw (2007)
found that the incidence of memory impairment following stroke is 50% within
the acute stage, reducing to 12% at 6 months post-stroke. In their study sample
Riepe, Riss, Bittner, and Huber (2004) found 74% were impaired on a brief
memory impairment test administered within 24 hours of stroke onset, and used
this data as the rationale for providing memory specific rehabilitation for those
patients. Other authors found a prevalence rate of 20% for memory impairment at
3 months post-stroke with varying degrees of severity of memory difficulties
(Ferro & Martins, 2001). In their sample of 60 patients with ischaemic stroke,
Usolteva, Dudarova, and Levin (2009), found a correlation at 6 months poststroke between delayed verbal recall and logical memory scores with functional
outcome (measured by the Rankin Scale). While different studies report the
21
presentation of memory problems at varying stages post-stroke, what does seem
apparent, however, is that generally the incidence of memory impairment
following stroke reduces over time as recovery occurs.
According to Cicala (1999), memory difficulties are more common when
the stroke has affected the temporal lobes or structures near the thalamus. In their
case study, Schott, Crutch, Fox, and Warrington (2003) also found thalamic
involvement for memory impairment, although the deficit was in the verbal
modality only. In a meta-analysis of memory impairment following right
hemispheric stroke, the authors found evidence of verbal and nonverbal memory
impairment thus challenging commonly held assumptions that the right
hemisphere stroke produces nonverbal memory deficits only (Gillespie, Bowen, &
Foster, 2006). Given the complex and extensive neural network involved in the
memory system, Lim and Alexander (2009) suggest that the anatomical bases for
impairments are most likely, quite variable.
Executive Functions
Executive functioning is an umbrella term used to encompass a set of
complex behaviours involved in the initiation, planning, sequencing, organisation,
and regulation of behaviour. Executive functions consist of distributed interactive
and overlapping networks and while mediated by structures of the frontal lobes,
are also believed to involve other cortical and subcortical regions of the brain
(Elliott, 2003; Sohlberg & Mateer, 2001; Stein, Harvey, & Macko, 2009).
Executive functions, are one of the most frequent domains of cognitive
impairment following stroke. There is speculation that deficits of executive
function are more prevalent in the early stages and indeed most of the available
data has derived from studies conducted at three months post stroke (Au et al.,
22
2006; Ballard, Rowan, Stephens, Kalaria, & Kenny, 2003; Leskela et al., 1999;
Stephens et al., 2004). Prevalence rates of between 40% and 52% have been
found (Blake, McKinney, Treece, Lee, & Lincoln, 2002; Pohjasvaara et al., 2002).
In a hospital-based study, Zinn, Bosworth, Hoenig, and Swartzwelder (2007),
found that the rate of executive dysfunction in the acute stage of stroke was about
50% in 47 confirmed stroke patients, although the study was limited by the
homogeneity of the sample, who were all relatively high functioning prior to the
stroke, and had mild strokes.
Not surprisingly, stroke survivors with poor executive functioning have been
found to have related to poorer outcomes from stroke (Barker-Collo, Feigin,
Parag, Lawes, & Senior, 2010; Zinn et al., 2007). Mok et al. (2004) found
impaired executive function but neither memory nor language impairment to be
associated with performance of complex activities of daily living (ADLs) at 3
months post-stroke. In another study of patients with mild vascular cognitive
impairment, Stephens et al. (2005) also found a decline in basic ADLs over six
years was associated with deficits of executive functioning as well as impaired
perceptual and spatial skills. Furthermore, those experience ongoing symptoms,
despite preservation of other cognitive domains, often have difficulty re-entering
the work force and indeed, adapting back into society in general (Caplan, 2005;
Ownsworth & Shum, 2008).
Most studies that have investigated stroke site location relative to executive
dysfunction, have found an association with the prefrontal lobe (Carey et al.,
2008), which is unsurprising given that this part of the brain mediates higher
cognitive thinking and behaviour (Alvarez & Emory, 2006). However, executive
dysfunction has been reported in stroke studies involving other areas of the brain
23
(Carrera, Michel, & Bogousslavsky, 2004; Espay & Jacobs 2010; Vataja et al.,
2003) thereby corroborating to some extent the evidence that executive function is
mediated by areas of the brain other than the frontal lobes.
Research has also identified particular domains of executive functioning as
being vulnerable to vascular disease or injury. For example, selective attention
and cognitive flexibility, set shifting, and response inhibition have consistently
yielded results that indicate a decline in performance when compared to base-line
measures or controls (Bombois et al., 2007; Garcia, Haron, Pulman, Hua, &
Freedman, 2004; Greve, Bianchini, Hartley, & Adams, 1999; Jokinen et al., 2005;
Lu & Bigler, 2000; Murphy et al., 2007; Prins et al., 2005; Sachdev et al., 2003;
Su, Wuang, Chang, Guo, & Kwan, 2006; Tang et al., 2009; Verdelho et al., 2007;
Zinn et al., 2007). Other specific areas of executive functioning compromised in a
stroke population are self-regulation (Amirian et al., 2010; Ownsworth & Shum,
2008), perseveration and problem solving (Su et al., 2006), working memory, and
processing speed (Zinn et al., 2007).
Research has consistently demonstrated an association between executive
dysfunction and depression (Channon, Baker, & Robertson, 1993; Mast, Yochim,
MacNeil, & Lichtenberg, 2004; Pohjasvaara et al., 2002; Tang et al., 2009; Vataja
et al., 2003). Narushima, Paradiso, Moser, Jorge, and Robinson (2007) found that
antidepressants had a positive effect in both recovery and preventing further
decline of executive functions in a stroke population. However, the sample in this
study was comprised of high socio-economic people thereby restricting the scope
to which their findings could be generalised.
24
Attention Deficit
Of all the cognitive domains, attention appears to be the most frequent and
prominent neuropsychological area affected in a stroke-related population
(Marshall, Grinnell, Heisel, Newall, & Hunt, 1997; Rao, Jackson, & Howard,
1999) with rates of up to 46% to 92% reported in acute survivors (Hochstenbach,
et al. 1998; Hermann et al., 2008; Hyndman, Pickering, & Ashburn, 2008;
Lesniak, Bak, Czepiel, Seniow, & Ionkowska, 2008; Nys, 2005; Patel, et al. 2002;
Tuhrim, 1993). The implications of an attention deficit are potentially farreaching given that attention is a precursor to other cognitive domains such as
memory and language, and influences other executive functions (Ben-Yishay,
Piasetsky & Rattock, 1987; Chen, Thomas, Glueckauf, & Bracy, 1997; Uomoto,
1992; White, 1992).
Some studies have investigated and distinguished impairment across the
different components of attention. For example, Marshall, Grinnell, Heisel,
Newall, and Hunt (1997) found significant impairment of divided attention in
their sample of stroke patients one year post-onset compared to non-stroke
controls and in a more recent study of older stroke patients, divided attention as
well as alternating attention were areas of poorer performance compared to the
performance of non-stroke patients (McDowd et al., 2003).
As with other areas of cognition, impaired attention abilities are also
reported to influence post-stroke rehabilitation outcomes (Barker-Collo & Feigin,
2006; Hyndman, et al., 2008; Sohlberg & Mateer, 2001). For example,
Robertson, Ridgeway, Greenfield, and Parr (1997) found that sustained attention
measured at two months post-stroke significantly predicted functional status in
individuals at two years post-stroke. Similarly, Nys (2005) found that cognitive
25
impairment at approximately one week post-stroke was a significant predictor of
quality of life at six months post stroke (as measured by the Stroke Impact ScaleSIS), with visual hemi-attention being a major contributing factor (beta= -.29, p<
.01). Indeed, attention as a key neuropsychological component in learning new
motor skills, particularly in the early stages of learning has been consistently
shown. For example, in one study, Stapleton, Ashburn, and Stack (2001) found
that attention deficits were common among acute hospitalised stroke patients, and
reported an association between distractibility, selective attention, balance, and
functional impairment. In another study investigating the associations between
attention, balance, function and falls in 48 community-based individuals with
stroke, Hyndman and Ashburn (2003) found significant correlations between
ADLs, balance and sustained and divided attention.
There is also an increasing bank of knowledge linking attention with social
functioning abilities. McDowd et al. (2003) found that impaired attention had a
negative impact on physical functioning and social outcomes in their sample of 55
older adults with ischaemic stroke. This area is particularly important in the field
of neuropsychological rehabilitation where the relearning of appropriate social
skills is often an objective (Addington et al. as cited in Combs & Gouvier, 2004;
Bellack, Gold, & Buchanan, 1999; Penn & Combs, 2000).
One manifestation of attention problems which may be observed following
stroke is hemineglect, also known as unilateral neglect, hemispatial neglect,
spatial neglect or hemi-inattention. It is characterised by the “failure to report,
respond or orient to novel or meaningful stimuli presented to the opposite side of
a brain lesion, when this failure cannot be attributed to either sensory or motor
defects” (Bailey & Riddoch, 1999; Churchland, 1989, p230). Most of the
26
cognitive dysfunction produced by hemi-inattention is because of an asymmetric
distribution of attention, either with respect to extrapersonal space or to an object
being viewed (Marshall, 2009). Hemineglect is a multimodal syndrome, usually
resulting from a stroke and can affect, to varying degrees, visual, auditory,
somatosensory and motor modalities in different combinations and severity
(Robertson & Marshall, 1993; Stirling, 2002), depending on the lesion location
(Mesulam, 1994). Visual neglect is the most common form of the disorder
although neglect of the limbs opposite the brain-damaged side is also frequently
seen. Both conditions for some result in serious rehabilitation difficulties (Hier,
Mondlock, & Caplan, 1983; Ogden, 2005; Wade, Wood, & Hewer, 1988).
While the syndrome usually manifests contralaterally, ipsilesional neglect has
been reported (Kim, et al., 1999; Schwartz, Barrett, Kim, & Heilman, 1999). In
their systematic review of 30 studies of contralesional unilateral spatial neglect,
Bowen, McKenna, and Tallis (1999) found that neglect occurred predominantly
with right brain damage as opposed to left brain damage. Indeed, Stirling (2002),
purports that left-sided hemineglect is far more common and more severe, a
finding that has been consistently observed in much of the previous literature
(Heilman, Watson, & Valenstein, 1993, 2003; Hildebrandt, Spang, & Ebke, 2002;
Kinsbourne, 1999; Vallar, 1998) giving rise to the hypothesis that the right
hemisphere plays a more dominant role in the attention process (De Renzi,
Faglioni, & Scotti, 1970). However, other explanations for this phenomenon,
view attention as a result of hemispheric physiological arousal or activation
(Heilman, et al., 1993) or that attention is a directional phenomenon with each
hemisphere having greater influence to the opposite side of space (Kinsbourne,
1977). In contrast, Ogden (1985) found no difference in lateralisation of
27
hemisphere for hemineglect. Reported incidence rates of hemineglect range from
10% to as high as 95%, with variation again, largely due to different
methodologies (Bailey & Riddoch, 1999; Bowen, McKenna, & Tallis, 1999;
Lopes, Ferreira, Carvalho, Cardoso, & Andre, 2007; Ringman, Saver, Woolston,
Clarke, & Adams, 2004; Schenkenberg, Bradford, & Ajax, 1980; Zoccolotti et al.,
1989).
Attention is also a key link to the re-learning of motor skills and successful
functional outcomes. It is a very basic function upon which other
neurological/cognitive functions are predicated and as such is a determinant of
positive outcomes in other cognitive areas (Barker-Collo, 2009; Hyndman et al.,
2008). It is this central role to recovery from stroke that provides the impetus and
incentive for further discussion of attention in this study.
Theories of Attention
Attention is considered by many to be a precursory foundation for other
more complicated cognitive skills such as memory and language skills (Cowan,
1995; Fisk & Schneider 1984; Langdon 2002; Whyte, 1992; Wood as cited in
Raskin & Mateer, 1994), and as such it may be reasonable to assume that
remediation of attention deficit needs to take place in order for other cognitive
domains to improve.
The upsurge of scientific research into attention in recent decades has
revealed a phenomenon that is so nebulous and complex that the common consent
is that most definitions of this cognitive domain are now inapt, with some even
arguing that a particular definition or description of attention is impossible (LeonCarrion, 1997; Manly, 2003). Despite those sentiments, many definitions of
28
attention have nevertheless been articulated since William James wrote about it in
1890 when he stated:
It is the taking possession by the mind, in clear and vivid form, of one out of
what seem several simultaneously possible objects or trains of thought.
Focalisation, concentration, of consciousness are of its essence. It implies
withdrawal from some things in order to deal effectively with others... (cited in
Jagadeesh, 2006, p. 195)
Although James identifies that there is a relationship between attention and
consciousness, even today the full extent of this relationship remains unclear and
elusive (Posner, 1994; O‟Regan & Noe 2001). Research at the neuronal and
molecular levels to understand the mechanistic basis of attention and
consciousness is required in order to gain a clearer understanding of the
relationship between these two distinct yet intimately close processes.
The dominance of behaviourist theories in psychology in the early twentieth
century meant a long delay before the first modern theory of attention developed.
In 1958 during the „cognitive revolution‟ (Harre, 2002), Broadbent presented the
first comprehensive model of attention based on the human information
processing approach. This work was largely built on and explained the dichotic
listening experiments conducted by Cherry in 1953. Broadbent‟s single-filter,
limited capacity model proposed that we could attend to only one stimulus at a
time because target stimuli receive priority over concurrent non-target stimuli
(Johnson & Wilson, 1980). That is, after an early low level perceptual analysis
based on physical attributes, information is passed into a temporary sensory buffer
where unattended information is simply lost and the one selected information is
29
then „evaluated‟ via a filtering process that determines whether or not that
information is passed into consciousness (Moray, 1995). (See Figure 1).
Perceptual
Attend
Input
Low Level
Perceptual
Analysis
Filter
Ignored
Semantic/
Meaning
Analysis
Figure 1. Early Selection Theory of Attention (Broadbent, 1957)
In a modified Early Selection Theory of attention, Treisman (1960)
proposed a two-channel model of selective attention thus expanding on
Broadbent‟s idea by proposing that non-attended stimuli are not completely
filtered out but attenuated according to their subjective importance (See Figure 2).
Treisman‟s model also emphasised the role that priming can have on
psychological processes.
Attend
Perceptual
Input
Ignored
Semantic/
Meaning
Analysis
Low Level
Perceptual
Analysis
Response
Filter
Figure 2. Modified Early Selection Theory of Attention (Treisman‟s Attenuator Theory)
Broadbent and Treisman‟s models were the first of the „Early Selection‟
models in which the locus of the bottleneck for processing information occurs
before the mind can analyze its semantic content i.e. at the perceptual level.
However, subsequent theories of „Late Selection‟ as developed by Deutsch and
Deutsch (1963), and Norman (1968) purported that all stimuli is analysed with
further processing afforded to pertinent stimuli just before entry into longer
30
lasting memory, effectively placing the locus of the bottleneck later in the process
continuum. (See Figure 3).
Perceptual
Input
All
Stimuli
Low Level
Perceptual
Analysis
Semantic/
Meaning
Analysis
Filter
Response
Figure 3. Late Selection Theory of Attention
At a time when the study of attention shifted from auditory to visual tasks,
partly because of the more precision in controlling visual stimuli, Kahneman
(1973) introduced his attentional resource theory that combined motivational,
attentional and arousal processes. He argued for a finite cognitive capacity to
devote to a task with each task requiring different capacity use. The number of
activities which can be performed is determined by the capacity each requires and
is controlled by a “central processor” that adjusts and allocates attention
accordingly. He predicted that as a skill becomes more automated, it becomes
more streamlined and takes up less of one‟s attentional capacity. However,
Kahneman‟s model did not address a person‟s ability for divided attention. It was
Allport‟s (1972) model of attention that provided a theoretical basis for this type
of attention. This model argued for several separate modules for different kinds
of input stating that attention can be divided between tasks that use different skills
(e.g. speech and pattern recognition), although not between similar tasks where
there is competition for resources from the same module (e.g. problem solving
and decision making).
However, the selectivity models were limited in that they did not address
the processing of information beyond the perceptual level. This lack of a more
comprehensive model of the attention process was undertaken in 1974 when
31
Baddeley proposed an influential model of working memory which began to
address the more comprehensive nature of attention. Baddeley‟s model included a
„central executive‟ that is primarily attentional in nature and responsible for
directing attention to and from either of its two „slave systems‟, the phonological
loop (verbal stimuli) and the visuo-spatial sketchpad (visuo-spatial stimuli) while
attention is temporarily shifted to other stimuli (See Figure 4). In 2000, Baddeley
subsequently added a fourth slave system, the episodic buffer to this model. The
purpose of the episodic buffer is to bind together all of the information from the
other components of working memory with information about time and order.
This assists in preparing memories for storage in episodic long term memory
(Baddeley, 2000).
Central
Executive
Phonological
Loop
Visuo-spatial
Sketchpad
Episodic
Buffer
Figure 4. Baddeley‟s Model of Attention (Baddeley, 2000).
Since the early models of attention were introduced in the 1950‟s, the
knowledge of attention has grown exponentially and many contemporary models
not only attempt to integrate the early and late approaches but also extend their
theory into the fields of neurophysiology, neuropsychology and computational
modelling. In the 1960s, neuroscientist, Robert Wurtz, when recording electrical
signals from the brains of macaques completing attentional tasks, was the first to
demonstrate a direct neural correlate with a mental process, namely enhanced
32
firing in the superior colliculus (Goldberg, 2007). In 1935, John Stroop had
published his work on the now famous Stroop Colour-Word task, although in the
behavioural climate of the time, this work had little impact in the world of
psychology. Stroop‟s work was „rediscovered‟ in the 1960s and subsequently the
Stroop effect has become one of the most valuable tools of cognitive psychology
providing a fuller understanding of how attention works (McLeod, 1991). More
recently, the utilisation of brain imaging technology has provided a functional
anatomy of the human attentional system and now most researchers conceive
attention as a system in which sequential processing occurs in stages that involve
different brain systems (Lezak, 2004). This multi-modality and multi-resourced
process explains, at least in part, why there is a lack of a common understanding
of this phenomenon.
However, none of the theoretical models have been produced for clinical
purposes to aid in the evaluation and remediation of attention deficit. Sohlberg
and Mateer (1987, 1989), provide a clinical model which incorporates current
theoretical thinking and is based on task performance, errors and subjective
complaints by individuals with brain injury. The authors identify five different
types of attention which are hierarchical in nature. Sustained attention is
considered the least complex component followed by selective attention, then
alternating attention and finally divided attention. The components of this model
are summarised in Table 1.
33
Table 1
Sohlberg and Mateer’s (1989) Clinical Model of Attention
Focused Attention
Sustained Attention
Selective Attention
Alternating Attention
Divided Attention
The ability to respond discretely to specific visual,
auditory or tactile stimuli.
The ability to maintain a consistent behavioural
response during continuous and repetitive activity.
The capacity to maintain a behavioural or
cognitive set in the face of distracting or
competing stimuli and therefore incorporates the
notion of freedom from distractibility.
The capacity for mental flexibility that allows
individuals to shift their focus of attention and
move between tasks having different cognitive
requirements.
This is the highest level of attention and it refers to
the ability to respond simultaneously to multiple
tasks or multiple task demands.
This chapter has provided an overview of the outcomes of stroke with a
more detailed review of the phenomenon of attention deficit following this
disease. This was followed by a summary of the evolution of attention theory.
The next chapter (Chapter 3) will begin with an explanation of cognitive
rehabilitation and a summary of the literature on its efficacy. This will be
followed by a review of the literature for cognitive rehabilitation narrowing to an
investigation and discussion on the evidence for rehabilitation of attention,
including APT. The closing stages of the chapter will provide a discussion of
what the barriers to trials in cognitive rehabilitation are and how they might be
overcome to ensure future high quality research into this area of health
rehabilitation.
34
“A journey of a thousand miles begins with a single step”
Lao Tzu
Chapter 3: Cognitive Rehabilitation
There are a multitude of definitions to describe cognitive rehabilitation and
Prigatano‟s (2005) explanation that it “refers to non-pharmacological and nonsurgical intervention by healthcare providers that aim to improve or restore
problem solving capabilities of brain function that have been disturbed by a
known or suspected brain lesion(s)”, (cited in Halligan & Wade, 2003, p3),
provides an indication of the diversity and complexity of this field of therapeutic
knowledge. Gaylins‟ (1977, p. 2) definition that “...the rehabilitation of a headinjured person is, principally, a task of aiding that person to speak and act in a
way which optimises his or her adaptability and sense of belonging”, also alludes
to the eclectic nature of the discipline. Indeed, Sohlberg and Mateer (2001),
advocate for a wider appreciation of the aims of cognitive rehabilitation to include
personal, emotional and social contextual variables in treatment plans and goals.
Nevertheless, within this holistic framework, there is a strong emphasis on the
retraining or alleviation of problems caused by cognitive “deficits in attention,
visual processing, language, memory, reasoning/problem solving, and executive
functions” (Sohlberg & Mateer, 1989, p. 4), as being fundamental to cognitive
rehabilitation. Cicerone et al. (2000) provide a more prescriptive definition of
cognitive rehabilitation as;
a systematic, functionally-orientated service of therapeutic cognitive
activities, based on an assessment and understanding of the person‟s
brain-behaviour deficits. Services are directed to achieve functional
changes by (1) reinforcing, strengthening, or re-establishing previously
35
learned patterns of behaviour, or (2) establishing new patterns of
cognitive activity or compensatory mechanisms for impaired neurological
systems. (p. 1696)
Tasks designed to reinforce or re-establish previously learned patterns of
behaviour or to establish new compensatory mechanisms for impaired
neurological systems are the mainstay of this approach. Cognitive rehabilitation
can be regarded as a particular aspect of the broader field of neuropsychological
rehabilitation, the latter being a method of restructuring lives in a social context
that does not represent training of cognitive abilities only but also includes
addressing emotional and psychosocial problems, particularly as difficulties in
these areas can exacerbate cognitive difficulties (Wilson, 2008) .
The discipline of cognitive rehabilitation has been practised for well over a
century with its origins lying in language recovery programmes developed by
Broca in the mid-1800s, for people with speech disorders. Modern cognitive
rehabilitation is, however, largely attributable to the work of physician Kurt
Goldstein (1942), who treated brain-injured German soldiers during World War 1
and recognised the importance of working with both cognitive and personality
processes simultaneously. Psychologist and physician, Alexandria Luria and
Neuropsychologist, Oliver Zangwill are two other important figures in the
evolution of cognitive and neuropsychological rehabilitation. Indeed, Luria has
become universally known as one of “the founding fathers of neuropsychology”
(Christensen, 1996, p. 279; Goldberg, 2009, p. 10). In her review of the history of
cognitive and neuropsychological rehabilitation, neuropsychologist, Freda
Newcombe, (2002), refers to Zangwill as the “Great Precursor” of clinical and
neuropsychological rehabilitation. During World War ІІ when working with
36
victims of missile wounds, Alexander Luria acknowledged the presence of
functional systems mediating cognitive functions located in different brain regions
(Ponsford, 2004), while it was Oliver Zangwill (1947), who first identified three
main approaches to rehabilitation including compensation, substitution and direct
training; methodology that continues to be widely practised in neuropsychology
today (Wilson, 1997). Indeed, the efforts of these two practitioners provide much
of the foundation and rationale for contemporary cognitive and
neuropsychological rehabilitation (Boake, 2003).
In the two decades spanning the 1980‟s and 1990‟s, against a backdrop of
consumer health reforms, an exponential amount of research into recovery from
brain injury took place and there now exists a substantial body of evidence to
support the effectiveness of cognitive rehabilitation for the improvement of
cognitive deficits following trauma to the brain (Cappa et al., 2005; Cicerone et
al., 2000; Kreutzer, 1999; Park, Proulx, & Towers, 1999; Ponsford, 2004;
Sohlberg & Mateer, 2001). Additionally, technological advancement has
accelerated improvement and growth of cognitive rehabilitation with published
research studies and neuroimaging of both humans and animals having
contributed to this store of data (Cicerone et al., 2005).
Knowledge of neuroplasticity, (the process by which neurons create new
connections among themselves), has risen dramatically since the notion was first
introduced in the 1950‟s by researchers who found that environment had an effect
on the structure and function of the animal brain. Evidence from functional
Magnetic Resonance Imaging (fMRI) studies provides compelling evidence of the
human brain‟s ability for reorganisation of structure and function (plasticity)
following pathology (Benton & Tranel, 2000). Furthermore, it is now known that
37
neuroplasticity is not the prerogative of the young but is a phenomenon that can
occur throughout the human lifespan, albeit more slowly as the organism ages.
Using functional Magnetic Resonance Imaging (fMRI), a small number of
researchers have found evidence of neural plasticity when testing for the efficacy
of cognitive rehabilitation in patients with Traumatic Brain Injury (TBI;Kim, Yoo,
Ko, Park, & Na, 2009; Laatsch, Thulborn, Krisky, Shobat, & Sweeney, 2004).
Recent insights into the neurobiology of repair after stroke also provide evidence
for the guidance of optimal prescription of therapeutic interventions (Cramer &
Riley, 2008). These preliminary findings of brain reorganisation following brain
trauma present potentially major implications for cognitive rehabilitation. In
principle, if neural circuits can be modified after injury, then it is feasible to
assume that functional change may also occur (Kolb & Gibb, 1999; Sohlberg &
Mateer, 2001).
Approaches to Cognitive Rehabilitation
The management of cognitive impairment is multi-faceted with different
problems presenting at various stages requiring different approaches. This section
will present an overview of the models of the more common approaches used in
cognitive rehabilitation today.
Models provide a rationale and a direction for increasing the specificity and
efficiency of clinician-targeted interventions. Bracy (1986), states “... a theory of
brain functioning and of rehabilitation is necessary for assessment diagnosis,
treatment planning, goal setting and providing therapy. Without a unifying and
guiding theoretical framework, our efforts would not amount to much more than
random stabs in the dark”. In his description of cognitive rehabilitation as “an
assortment of procedures to improve or restore a diverse collection of abilities and
38
skills”, Wood (1990, p3), identified four main approaches for those procedures as
being; restorative, compensatory, environmental, and behavioural. These
approaches had been alluded to much earlier when Zangwill (1947) proposed
substitution (therapy in which a substitute substance is used) , restoration and
compensation as the three activities that constitute cognitive rehabilitation.
Mateer, Kerns, and Eso (1996), identified three broad categories for the
management of attention and memory impairments in children following
traumatic brain injury. The first approach is externally focussed in that it attempts
to alter aspects external to the individual. The second approach is designed to
improve or restore cognitive abilities, and the third category involves the training
and implementation of procedures or strategies that compensate or lessen the
functional impact of cognitive deficits. The second two approaches can be
considered internally based as they are designed to directly change the
individual‟s abilities and/or behaviours. The four approaches widely utilised in
cognitive rehabilitation are:
Restorative Therapy.
Restorative Therapy is based on the theory that systematic repetitive
exercises can restore lost functions which have been identified by
neuropsychological or psychometric assessment (Cicerone & Tupper, 1990;
Coelho, De Ruyter, & Stein, 1996; Sohlberg & Mateer, 1989). This approach is
most effective when the remediation has been tailored to address the pattern of
deficits of the particular individual. Such exercises are available in the Attention
Process Training programme which is based on a clinical model of five
components of attention; namely focussed, sustained, selective, alternating and
divided attention (Sohlberg & Mateer, 1989). An example of a task designed to
39
improve sustained attention requires listening for target letters or numbers on an
attention tape and pressing a buzzer when the target is identified. Pretesting
identifies the appropriate level at which therapy starts and the parameters of the
exercises (e.g., complexity, quantity, speed of presentation, or the amount of
cueing given) are incrementally modified in accordance with „mastery‟ of each
exercise, thereby extending the goal of therapy (Ponsford, Sloan, & Snow, 1995).
Thus, the more basic processes of attention are trained before attempting the more
complex processes. The goal of restoration therapy is for the patient to perform
the activity in the same way and using the same functions whether it is cognitive,
motor or perceptual (Shiel, 2003).
Compensatory Therapy.
Compensatory therapy in contrast, strives to improve functioning by
recruiting relatively intact cognitive processes to fulfil the role of impaired
functions or by using external prosthetic aids (e.g., diaries, and social supports) to
compensate for the loss of function (Liberman, 2008). Visual mnemonics is a
common effective strategy used in the treatment of impaired verbal memory
(Wilson & Evans, 2003). An example of a verbal mediation strategy often used is
the PQRST (Preview, Question, Read, State, and Test) method which requires
deeper processing of the material. The assumption underlying this technique is
that the broader encoding will enhance later recall (Barker-Collo & McCarthy,
2007). Generally, restorative techniques are used to focus on the patient‟s
weaknesses, while compensatory techniques are often driven by a person‟s
strengths.
40
Environmental Therapy.
Environmental therapy in the acute stage of rehabilitation involves
modification of the individual‟s environment with much of the focus being on
safety. In later stages of recovery the therapist often engages with family members
and others in order to tailor the environment so as to facilitate adaptive learning.
For example, individuals with significant memory or executive function deficits
may benefit from an environment that is clutter-free and has been manipulated
with cues such as labelling, a central message centre, and posting checklists
reminders, to initiate a certain behaviour, or clocks and calendars for orientation
purposes (Mateer, 2005).
Behaviour Therapy.
Behavioural approaches are advocated by some authors who have found
some success when working with neurologically damaged patients (Cotrell, 1997;
Goldstein & Ruthven, 1983; Wilson, Herbert, & Shiel, 2003). Behaviour therapy
encompasses a diverse range of procedures to attain its overall aim which is the
modification of behaviour. In patients who have been cognitively compromised,
task-specific, simple-response behavioural techniques such as token reinforcement
have been shown to be effective (Goldstein & Ruthven, 1983). For example, in
an auditory listening task, the person receives a token for each correct response
and is fined a token for each incorrect response. All participants in a study using
this procedure demonstrated improved performance of sustained attention and
more efficient information processing ability (Wood, 1986).
However, a major challenge for any rehabilitation specialist is to motivate
the patient to engage in therapy and when working with neurologically or
psychologically compromised patients, this goal can be particularly difficult to
41
achieve (Marin & Chakravorty, 2005; Prigatano & Fordyce, 1986). Motivation is
often a problem of executive dysfunction as patients may lack insight into their
condition (anosognosia), and because of this reason these individuals are
sometimes excluded from cognitive therapy. However, such problems do not
necessarily constitute a barrier to the effective use of behaviour therapy (Sohlberg
& Mateer, 2001). Indeed, Craighead, Kazdin, and Mahoney (1976), Lietenberg
(1976), and Goldstein and Ruthven (1983), all found behaviour therapy to be
effective with people who present with aggression, anxiety, depression or who are
non-compliant (Horton & Howe, 1981; Turner, Green & Braunling-McMorrow,
1990), difficulties that are frequently present, in varying combinations, in people
who have suffered TBI.
However, many aspects of rehabilitation modes of therapy overlap and it is
not unusual for therapists to adopt more than one approach (Ylviskaer & Feeney,
1998). Indeed, Wilson (2005) suggests that because models of cognitive
rehabilitation are always evolving and often draw on many fields of psychology, it
would be prudent for clinicians to utilise more than one approach. Multiple
approaches may become particularly pertinent as therapy progresses, and the
needs of the individual change with improved functioning, resulting in the
renegotiation of the goals of rehabilitation.
Nonetheless, a number of psychologists are critical of some
neuropsychological and cognitive rehabilitation models for the lack of a
relationship with daily-tasks and functional capacities. Wilson (1997, 2008), for
example, disapproves of cognitive neuropsychologists who typically treat the
impairment rather than the disability and asserts that any reduction in impairment
needs to be demonstrated in a reduction of disability if it is to be of any use to the
42
patient. The World Health Organisation defines impairment as “a limitation of a
physical or mental function because of disease or injury” and disability as “the
loss of the ability to participate in some activity because of an impairment”
(Schefft, Malec, Lehr, & Kanfer, 1997, p238). The National Institute of
Neurological Disorders and Stroke (NINDS) impressed the need for a paradigm
shift from one focussing on diagnosis and descriptive analysis of
neuropsychological assessment and cognitive impairments towards a linking of
diagnosis and interventions that improve functional outcomes (Paolucci, et al.,
1996).
Similar sentiments have been conveyed by other researchers (Cicerone, et
al., 2005; Rohling, Faust, Beverly, & Demaki, 2009; Uzzell, 2000). Prominent
pioneers of the holistic approach to neuropsychological rehabilitation include
Goldstein (1942), Luria (1963), Ben-Yishay (1975), Diller (1976), and Prigatano
(1986). In addition to the battery of therapeutic interventions for neurologically
impaired patients, the provision of psychotherapeutic interventions as an
important key ingredient to assisting both patients and their families deal with
their personal emotional distress is widely recommended (Christensen, 2000;
Leathem & Christianson, 2006; Prigatano and Ben-Yishay, 1999; Sohlberg &
Mateer, 2001).
Other factors can also influence the success of the intervention. For
example, many clinicians and researchers in the field of neuropsychological
rehabilitation advocate for an individualised programme designed and managed
by a multi-disciplinary team. This tailored approach considers personal aspects
such as time post-injury/onset, the preferred learning style, cognitive status,
emotional and personality factors both before and after injury, the type of injury
43
sustained, co-morbidity, motivation, age and education, and the role of the family
and significant others including employers (Christensen & Uzzell, 2000). It is
also important that the characteristics of the treatment programme incorporate
duration, intensity, frequency and the setting of the programme.
As neuropsychological rehabilitation is becoming a more standard
component of care after brain injury, ongoing research to achieve better
understanding of how cognitive rehabilitation interventions improve recovery and
functioning, is needed. The following section will provide a summary of the
major publications available in the literature that have attempted to investigate the
quality of cognitive rehabilitation.
Efficacy of Cognitive Rehabilitation
The steep rise in neuropsychological research and cognitive rehabilitation has
generated a large number of reviews and analyses evaluating the effectiveness of
its use with individuals who have suffered neurological insult, over the last
decade. Overall the information that follows demonstrates that while cognitive
rehabilitation is not without its critics or inconsistencies there has nevertheless
been an accumulation of evidence suggesting that it does have value in the
rehabilitation process.
Influential investigations that have produced positive findings for cognitive
rehabilitation date back to 1999, when the European Federation of Neurological
Societies (EFNS), Task Force on Cognitive Rehabilitation was established for the
purpose of producing recommendations for neurological practice. In their review
and subsequent update of the literature on cognitive rehabilitation, the EFNS
found evidence, albeit limited, to support cognitive rehabilitation for visual
neglect and apraxia after stroke, attention deficit after TBI, and memory
44
dysfunction after either TBI or stroke (Cappa et al., 2003; Cappa et al., 2005). In
the same year Carney et al. (1999) in their systematic review of the literature, also
found evidence for a domain-specific effect, namely memory for cognitive
rehabilitation.
Further evidence promoting cognitive rehabilitation was published in Park
and Ingles‟ (2001) meta-analysis of the efficacy of 30 studies using interventions
for attention disorders following brain damage. Unlike systematic reviews, a
meta-analysis requires that effect size for each study is included and as such
provides statistically rigorous data integrated from across studies (Egger & Smith,
1997). The authors‟ analysis concluded that acquired deficits of attention are
treatable using specific-skills training, although they found that the learning that
occurred did not generalise to tasks outside those used in training (Park & Ingles,
2001).
Furthermore, in 2000, the American Congress of Rehabilitation Medicine‟s
(ACRM) published a comprehensive review of the literature of evidence-based
cognitive rehabilitation for the purpose of providing evidence-based practice
guidelines for persons with brain injury (Cicerone et al. 2000). This review was
updated in 2005 (Cicerone et al. 2005). These reports evaluated the results of
studies of cognitive rehabilitation versus alternative treatments and found that
approximately 79% of the comparisons demonstrated a benefit of cognitive
rehabilitation over the alternative treatment (Cicerone et al. 2005). Indeed, such
was the influence of the review, that The Brain Injury Interdisciplinary Special
Interest Group of the ACRM published practice guidelines with an emphasis on
the findings of these two reviews. In the 2005 review, Cicerone and his
colleagues declared that “there is now a substantial body of evidence
45
demonstrating that patients with TBI or stroke benefit from cognitive
rehabilitation” (p. 1689).
A meta-analysis of the systematic reviews of Cicerone et al. (2000, 2005),
was conducted by Rohling et al. (2009) which yielded reasonably positive
conclusions. The analysis of the 97 studies found the effects of cognitive
rehabilitation on global cognitive function to be relatively modest yet statistically
significant with treatment effects moderated by time post-injury, type of brain
injury, and age. The strongest evidence to emerge from the analysis was for the
effectiveness of attention training after TBI and cognitive training of language and
visuospatial deficits for aphasia and neglect syndromes after stroke. It was also
concluded that visuospatial training tended to improve performance in other
cognitive domains. However, the authors did not find any evidence to support
memory training as being effective or any treatments that attempted to improve
holistic cognitive problems. As a result of this analysis the authors went on to
make recommendations for clinicians to focus their efforts on direct cognitive
skills training (Rohling et al., 2009).
A number of recent studies have attempted to establish the effectiveness of
cognitive training for memory, attention, perception and language in older adults
with mild cognitive impairment (MCI) who are at risk of developing Alzheimer‟s
or other types of dementia. In her review of seven of those studies Belleville
(2008) found that six reported positive results although variability in research
design and heterogeneity of the MCI population undermined those findings. This
flaw in the methodology prompted the author to emphasise the need for studies
that use larger samples of participants and randomised controlled designs.
46
Less conclusive findings regarding the efficacy of cognitive rehabilitation
have also been published. For example, a Cochrane review of the literature to
evaluate the effectiveness of cognitive training on attention deficit following
stroke was published by Lincoln and colleagues in 2000 (Lincoln et al., 2000).
The authors‟ findings were somewhat tentative in that although they found
attention training improved alertness and sustained attention, only two studies
were evaluated and in neither study was the assessment of outcome carried out
blind to the intervention. Furthermore there was insufficient evidence to support
or refute the effect of attention training on functional abilities. In two other
separate Cochrane reviews of the literature on memory rehabilitation following
stroke, the authors were unable to find evidence to either support or refute the
effectiveness of such treatment (Majid, Lincoln, & Weyman, 2002; Nair &
Lincoln, 2007). A more recent review of the literature also found inconclusive
evidence for or against cognitive approaches for recovery of memory following
stroke (Coulas, 2007).
However, despite its critics and controversy, cognitive rehabilitation has
become a standard component of rehabilitation after neurological trauma,
particularly traumatic brain injury (Rohling et al., 2009). Overall, the evidence
for the efficacy of cognitive rehabilitation is positive thereby providing
confidence not only for its inclusion in rehabilitation programmes but also for
providing impetus for further research. However, in the current era of evidencedbased practice, further research needs to be more scientifically rigorous with class
1 evidence (randomised control trials). The question of whether or not cognitive
rehabilitation should aim to reduce impairment or compensate for the impairment,
are issues that also need further investigation. Moreover, given the vast array of
47
cognitive impairment, future research into specific cognitive areas such as
attention, memory, visuospatial skills, and executive functioning is essential.
Cognitive Rehabilitation following Stroke
The focus of stroke rehabilitation tends to be on remediation of physical
deficits; language/speech therapy; and to some extent functional activities that,
though impacted by cognition, are treated without a focus on their cognitive basis.
This is despite the finding that long-lasting neuropsychological sequels; such as
deficits in attention, planning, problem solving, memory, and speed of
information processing; occur in nearly half of stroke survivors. For example,
using measures of overall cognitive status (e.g., Mini Mental Status Exam;
MMSE; Folstein, Folstein, & McHugh, 1975), it has been reported that the
majority of individuals referred to in-patient rehabilitation (55.2%) will exhibit
cognitive deficits, with many individuals obtaining scores at or near the cut-off for
cognitive impairment (Bonita et al., 1997). Unfortunately, the general nature of
measures such as the MMSE does not allow them to provide an understanding of
the complex and heterogeneous nature of post stroke cognitive deficits (Donovan
et al., 2008).
In addition to their prevalence, there is evidence that neuropsychological
factors play a significant role in determining functional outcomes after stroke with
some arguing that cognitive impairment is more of a determinant of outcomes
than physical disability (Bays, 2001; Hochstenbach et al., 1998; Heruti et al.,
2002; Labi, Phillips, & Greshman, 1980; Paolucci et al., 1996; Robertson,
Ridgeway, Greenfield, & Parr, 1997; Zhu et al., 1998), and primarily accounts for
strain in stroke caregivers (Zak, 2000). This accumulating body of evidence
48
strongly suggests that appropriate neuropsychological rehabilitation may improve
functional outcomes and reduce the burden of stroke.
In an initiative to understand the impact of cognitive deficits and functional
recovery after stroke, NINDS and the Canadian Stroke Network have established
domains for studying „functional cognition‟ following stroke. The ten functional
cognitive domains identified include; language, reading and writing,
numeric/calculation, limb praxis, visuospatial function, social use of language,
emotional function, attention, executive function and memory. It is within these
realms that the impact of stroke on daily activities can be evaluated leading to an
increase of the potential benefits of rehabilitation and accordingly enhancing the
ecological validity of neuropsychological assessments (Donovan et al., 2008).
Evidence for Rehabilitation of Attention
Attention is one of the specific domains where there is a pressing need for
further research given the prevalence of attention deficits in post-stroke
impairment. Furthermore, attention is inextricably involved with memory and
executive functioning and is sub-served by shared neural circuitry (Sohlberg &
Mateer, 2001). Impairment of this domain sometimes leads to problems of a
wider and more complex nature which makes attention deficits one of the greatest
impediments to rehabilitation.
In their review of the literature of attention rehabilitation following stroke
and TBI, Michel and Mateer (2006), included three major approaches in which to
present their findings. The first approach embraces the adoption of a specificskills training regime. That is, people with an attention deficit learn or relearn
how to perform specific skills of functional significance, with the underlying
rationale of developing alternative neuropsychological processes that rely on
49
preserved brain areas, to improve performance of the skill (Carpenter, 2001). The
second approach is the so-called “direct route” that requires the patient to practice
abstract cognitive exercises designed to directly restore impaired attention
processes. The third approach may be more relevant further along in the
rehabilitation process, when the patient reintegrates into the home or work
environment. This approach focuses its efforts on environmental modification,
developing self-management strategies and building environmental support.
However, in practice, interventions from a combination of approaches are often
utilised to address the fluid, multi-faceted needs of the patient (Michel & Mateer,
2006).
The question that needs to be addressed is why then, given the extent of
post-stroke attention deficits and impact on functional outcomes, have there been
so few good quality controlled trials of cognitive rehabilitation for attention? In
the Cicerone et al. (2005) updated review of the literature for evidenced-based
cognitive rehabilitation of people with traumatic brain injury and stroke, only 17
of the 87 studies evaluated were Class I design (i.e., well-designed, prospective
Randomised Control Trials (RCTs) and of these only two looked specifically at
remediation of attention deficits.
The primary objective of intervention studies is to determine whether or not
a particular treatment is effective in bringing about positive change in a given
population. In accordance with the American Academy of Neurology 2004
criteria, the highest level of evidence (Class I study) comes from RCTs (Sacco et
al. 2006). The degree to which changes occurring during any study can be
attributed to the treatment of interest depends on the extent to which the research
is able to control for alternative explanations. Control may be exerted, for
50
example, by making sure that the individual(s) who conduct baseline and followup assessment are blind to the recipient of the treatment, by being explicit in
defining the sample population, using reliable measures, and providing a detailed
account of the treatment employed (Coolican, 1994). Class II studies are those
which do not randomly assign participants to treatment conditions, but meet all
other requirements of an RCT. These studies include masked outcome assessment
and are termed prospective matched group cohort studies (Chalmers et al., 1981;
Matthews, 2006).
The following section will present evidence from studies which evaluated
attention rehabilitation interventions following stroke. Attention was selected as
the area of deficit on which to focus because it allows examination of
interventions that are geared towards addressing attention more generally,
including interventions for visual neglect and other specific forms of attention
deficit. There are also products designed for the rehabilitation of attention deficits
that have been commercially available for a number of years, but have not yet
been robustly evaluated in this population.
For the sake of clarity, scanning and general attention interventions will be
discussed separately. A literature search of studies investigating scanning
interventions used for visual neglect was carried out. PsychInfo and the Cochrane
Data Base were the search engines used with the keywords: unilateral neglect,
attention, brain injury, stroke, CVA, scanning, rehabilitation, and cognitive
rehabilitation. Visual neglect is strongly associated with impairments of the
ability to sustain attention (Posner, 1993). The aim of scanning strategies is to
compensate for difficulties attending to the left by encouraging full scanning of
the environment (Bowen & Wenman, 2002). A summary of these studies is
51
presented in Table 2. As the focus here is on cognitive rehabilitation,
pharmacological interventions were not reviewed.
A summary of the twenty three papers of scanning interventions examined
in Table 2 cover fourteen randomised controlled trials (RCTs), eight controlled
clinical trials (CCTs) and one pre-post design. All studies recruited stroke
patients with unilateral neglect. Outcome measures cover a wide range of
domains of impairment including neglect, scanning ability, visual attention,
cognition, disability, functional abilities, and activities of daily living and some
well-known measures such as the Barthel Index, the WAIS and various
cancellation tests were used. Generally, sample sizes were small with the largest
study providing outcome data on 80 participants. Those studies, using measures
of overall functioning such as activities of daily living and functional outcomes,
consistently show improvements in level of disability and or independence.
However, the findings for neuropsychological outcomes are less consistent.
Limitations in methodology was an issue raised by Bowen and Wenman
(2002) when they concluded that only three out of the fifteen studies they
reviewed were sufficiently well-designed and controlled to provide conclusive
evidence for the effectiveness of attention rehabilitation.
52
Table 2
Studies evaluating scanning interventions for neglect
Authors
Design & Sample
Bowen, and Wenman,
SR & MA of 15 studies
(2002)
RCT = 8.
CCT = 7.
N = 400
10 studies from
rehabilitation
5 studies from hospital
admission
Robertson, McMillan,
MacLeod, Edgeworth,
and Brock, (2002)
Only 3 given A grade.
RCT
N = 39
Right hemisphere stroke
with left neglect, right –
handed, from in and
out-patient
rehabilitation.
Interventions
Any activity to reduce neglect or
resulting disability vs alternative
treatment or no treatment. Drug trials
were excluded. Therapy length varied
from <2 to 30 hrs.
Several provide no detail about the
intervention.
Outcome measures
Impairment (e.g., line cancellation
or bisection); disability (Barthel,
FIM, ADL); discharge setting (home
or not)
Conclusions
Impairment level improved
significantly and these effects
persist. Insufficient evidence for
impact on ADLs or discharge
setting. Few studies examined
disability / participation.
12 x 45 minutes of: (1) n = 19 Limb
Activation Device (LAD) - worn on
wrist, makes auditory tone if no left
movement made + Perceptual Training
(PT) – workbook exercises (e.g.,
visuospatial puzzles)
At post-treatment and 3-month
follow-up: Barthel, self- and otherratings of neglect, Motricity Index,
BIT, Comb & Razor personal
neglect tests, Modified landmark
test.
Significant Time x Treatment effect
on Motricity Index at 18-24 months
with LAD+PT performing better
than PT only. Analyses used are
questioned.
(2)n = 19 PT only + placebo LAD
At 18-24 month follow-up:
Nottingham Extended ADL,
Motricity Index, Balloons test, selfand other- ratings of neglect.
Post-treatment: Barthel, Edmans
Extended ADL, RPAB, RMA Gross
Functioning Scale
≥7 Hodgkinson Test for
Dementia
Edmans and Webster,
(2000).
RCT
N = 80 from a larger
RCT of consecutive
stroke admissions, mean
34 days post onset.
6 weeks x 2.5 hours per week
(1) n = 40 Transfer of training to „treat
the cause‟ of perceptual problems
(2) n = 40 Functional treatment of
„symptom rather than cause‟
Improvement in perceptual abilities
not related to group.
53
Weinberg et al. (1977)
Young, Collins, and
Hren, (1983)
Robertson, Gray,
Pentland, and Waite,
(1990)
RCT
N=32 Experimental
group 25= Control
group
Stroke patients with
right-brain injury
≥4 weeks post injury
CCT
Non-randomised, notblinded
N = 27 right hemisphere
stroke with left visual
neglect assigned to 3
different groups
RCT
N = 36 with behavioural
inattention, 32 poststroke, remainder with
head trauma or
meningioma
Wiart et al. (1997)
RCT
N = 22 < 3 months post
stroke
Antonucci, Guariglia,
and Judica, (1995).
RCT
N = 20 ≥ 2 months post
right hemisphere firstever stroke
20 hours graded intervention designed
to train compensation for impaired left
sided scanning abilities vs standard
rehabilitation
Scanning ability
Achievement test – reading tasks
Treatment resulted in significant
improvement on measures of
scanning and academic reading tests
thought to rely on scanning ability.
All receive 1 hr treatment/day for 20
days
Gp 1) Standard OT
Gp 2) 20 minutes Standard OT + 20
minutes paired cancellation + 20
minutes visual-scanning training
Gp 3) 20 minutes cancellation + 20
minutes visual-scanning training + 20
minutes block-design training
Control Group (N=16) 14 x 75 minute
sessions over 7 weeks of unspeeded
computer activities.
WAIS- Digit Symbol Coding, Block
Design, Picture Completion, Object
Assembly; letter cancellation;
WRAT Reading test; copying an
address and counting faces.
Groups 2 and 3 improved
significantly on visual scanning,
reading and writing compared to
group 1, with group 3 showing
greatest improvement.
WAIS, Neale Reading Test, letter
cancellation, ROCF, observer
reports; BIT (primary outcome)
No significant changes on the BIT
for either group although controls
showed greater improvement at 6
months than the experimental group
Battery of tests of neglect (e.g.,
bells, line cancellation) and FIM
Improvement of those in
experimental group was significantly
better than in controls for both
neglect and FIM tests.
At end of neglect treatment there
was significant improvement that
generalised to everyday life.
Experimental Group N=20) 14 x 75
minutes sessions over 7 weeks
4 levels of speeded scanning training
using touch screen
1) traditional stroke rehabilitation
2) usual care + 20 hours over 1 month
of visual scanning with trunk-control
rotation
Group 1) 2 months of neglect treatment
Group 2) General cognitive stimulation
for 2 months, then rehabilitation
training for neglect for 2 months.
Standardised test battery and
functional scale
54
Bergego, et al. (1997)
Pre-post
N = 7 right hemisphere
ischemic stroke
45 mins per day for 2 weeks on each
task:
1) Visual Scanning Training;
2) Level Comparison of 2 vertical bars;
3) Dynamic visual matching to sample
4) 150 words text reading.
Scene drawing, 3 cancellation tasks,
letter cancellation, line cancellation,
bells test, writing 5 lines.
No specific treatment effects on
static paper and pencil or
computerised tests.
Two computerised tasks using
words or non-words and
determining if 2 stimuli are
same//different
ADL = Activities of Daily Living, BDAE = Boston Diagnostic Aphasia Examination, BIT = Behavioural Inattention Test, CCT = Controlled Clinical Trail, FIM = Functional
Independence Measure, MA = Meta-analysis, MIT = Melodic Intonation Therapy, OT = Occupational Therapy, PASAT = Paced Auditory Serial Attention Task, PT =
Physiotherapy, RCPM = Raven‟s Coloured Progressive Matrices, RCT = Randomised Controlled Trial, RH = right hemisphere; RMA = Rivermead Motor Assessment;
ROCF = Rey Osterreith Complex Figure, RPAB = Rivermead Perceptual Assessment Battery, SR = Systematic Review,; WAIS = Wechsler Adult Scale of Intelligence,
WRAT = Wide Range Achievement Test
55
In contrast to the studies addressing visual neglect only, three RCTs, one
CCT and three pre-post design studies were found which examined more general
attention rehabilitation, five of which had small samples (N<39). These are
summarised in Table 3. Two trials involving general attention training, reported
significant improvements in alertness (Sturm & Willmes, 1991) and sustained
attention (Schottke, 1997), although these improvements were not reflected on
measures of functional independence. Using computerised attention training,
however, the experimental groups performed better on tests related plausibly to
attentional functions (Gray et al., 1992; Schottke, 1997; Sturm et al., 1997; 2004).
A programme consisting of hierarchical linguistic and non-linguistic tasks
targeting sustained, selective, and alternating attention resulted in improvement on
a measure of aphasia and a measure of abstract reasoning when compared to
baseline performance (Helm-Estabrooks, Connor, & Albert, 2000). Only one
study failed to produce an encouraging outcome. In the Mazer et al. (2003) study,
two different visuo-perceptual training techniques, resulted in no significant
differences, although the lack of a no-treatment or standard care control group
means that it is not possible to determine if either intervention might have been
equally and significantly effective. Otherwise, of the eight studies outlined in the
table, seven provide encouraging evidence for the positive effects of general
cognitive interventions for individuals with attention deficit.
56
Table 3.
Studies evaluating general attention interventions
Authors
Sturm and Wilmes
(1991)
Design and Sample
RCT
N = 27 (LHD)
8=(RHD)
Interventions
14 x 15 min sessions over 3 weeks
WDG and Cognitrone Training
programme for attention and perceptual
speed
17 received 14 sessions x 75 mins
computerised attention training vs 14
received 14 sessions x 75 mins
recreational computing
Outcome Measures
10 standardised psychometric tests
similar to the training procedure
Gray, Robertson,
Pentland, and Anderson,
1992
RCT
N = 31TBI patients with
attention deficit ≈ 20
months post-stroke
Sturm, Willmes, Orgass
and Hartje (1997)
Pre-post design
N = 38 with left and
right hemisphere
vascular lesions >
2months post-onset
2 x14hrs computerised training
programme
Improved Intensity and Reduced
Response Time and Error Rate on
Attention Tasks
Schoettke (1997)
CCT
N = 29 no blinding,
matched allocation
38-52 days post-stroke
Computer, paper pencil, and scanning
training 13 sessions over 3 weeks vs.
standard care.
Measure of sustained attention
Barthel Index
Helm-Estabrooks,
Connor and Albert
(2000)
Pre-post design
N = 2 LH stroke
patients with aphasia
>12months post- onset
Case 1=17 twice weekly sessions ATP
plus 16 sessions of MIT
BDAE, RCPM
Mazer, Sofer, KornerBitensky, Gelinas,
Hanley and WoodDauphinee, (2003)
RCT
N = 84 referred for
driving evaluation
Case 2=16 twice weekly sessions ATP
only
20 sessions of “field of view” training
of visual processing speed, divided
attention compared to traditional
computerised visuoperceptual training
PASAT, Arithmetic, Picture
Completion, Digit Span subtests of
The WAIS-R, word fluency, WCST,
finger tapping, GHQ
On-road driving test,
visuoperceptual tests and TEA
Conclusions
Attention training improves alertness
(Standard mean deviation 0.77, 95%
CI 0.21 to 1.33); sustained attention
(SMD 1.03, 95% CI 0.44 to 1.61).
Improvement of those in
experimental groups was more
significant on the PASAT and
Arithmetic subtest and GHQ.
There were significant specific
training effects for both intensity
aspects (alertness and vigilance), and
also for response time in the
selective attention and error rate in
the divided attention task.
Significant effect on sustained
attention.
No evidence to draw conclusions
about information processing or
ADL.
Significant improvement on both
measures for both patients.
No difference in driving skill, some
benefit for those with right
hemisphere lesions.
57
Sturm et al. 2004
Pre-post
Grp 1 (N = 4) computerised alertness
TAP, PET/fMRI
3 ppts in Gp 1 improved on alertness
N = 8 right-handed
training
compared to only 1 of Gp 2. Scans
right-hemi vascular
Grp 2 (N = 4) memory training
showed restitution of the RH
lesion patients
Both groups received 14 x 45min
observed in ppts with behavioural
>5 months post stroke
sessions over 4 weeks
improvement
ADL = Activities of Daily Living, ATP = Attention Training Programme, BDAE = Boston Diagnostic Aphasia Examination, CCT = Controlled Clinical Trail, fMRI =
functional Magnetic Resonance Imaging, GHQ = General Health Questionnaire, LHD = Left Hemisphere Damage, PASAT = Paced Auditory Serial Attention Task, PET =
Positron Emission Topography, RCPM = Raven‟s Coloured Progressive Matrices, RCT = Randomised Controlled Trial, RH = Right Hemisphere, RHD = right hemisphere
damage; TAP = Test of Attentional Performance; TEA = Test of Everyday Attention, WCST = Wisconsin Card Sorting Test, WDG = Wiener Determinationsgerat; WAIS =
Wechsler Adult Scale of Intelligence,
58
However, none of the studies reviewed, targeted the entire range of the
different types of attention (i.e. focussed, sustained, selective, alternating and
divided attention) in a single rehabilitation package. This is at odds with the
availability of attention rehabilitation packages such as Sohlberg and Mateer‟s
(1987) Attention Process Training (APT), which was designed for the remediation
of attention and memory disorders with mild, moderate and severe brain injury.
The APT is based on a theoretical model to facilitate attention as a comprehensive
and multilevel functional process (Sohlberg & Mateer 1987) comprised of
sustained, alternating, selective and divided attention and the APT programme
provides the opportunity for addressing each of these particular aspects of
attention. (See Table 1 Sohlberg and Mateer‟s Clinical Model of Attention). It
has been evaluated within brain injured samples, including some post-stroke
individuals.
It has been claimed that specific components of attention require specific
training in order for improvement to occur (Sturm & Willmes, 1991; Sturm et al.,
1997). Thus, APT treatment involves a group of hierarchical organised tasks that
place increasing demands on the individual as they progress through the
programme. Examples of exercises include auditory tapes such as listening to
descending letter sequences, detecting target stimuli with the presence of
distractor noise or complex semantic categorisation tasks requiring switching sets.
A combination of both auditory and visual activities are utilised on a number of
tasks. Progression through one module builds skills that are thought to be
necessary for performing in subsequent modules (Sohlberg & Mateer, 2001).
Sohlberg, Johnson, Paule, Raskin, and Mateer (2001) published the APT-II for
59
use with adults with attention and memory disorders and mild cognitive
impairment.
Studies conducted to evaluate the efficacy of APT-I and APT-II are
presented in Table 4. Of the 12 studies, two were RCTs, two CCTs and eight
were Pre-Post Designs. The studies recruited participants who had experienced a
range of neurological illness including four studies with TBI patients, two with
patients with Cerebral Vascular Accident, one study with both TBI and CVA
participants and one study with a patient with Attention Deficit Disorder. Injury
or illness was greater than two months post-onset. The four remaining studies
included participants with schizophrenia or aphasia. Thus a range of participants
have been evaluated with this intervention. All participants were identified as
having an attention deficit by neuropsychological testing or self-assessment. The
amount of APT provided to subjects varied considerably across studies ranging
from 15 sessions to 85 sessions with no apparent relationship between the number
of sessions and participant‟s performance on measured outcomes. Eleven of the
twelve studies concluded a positive outcome for the remediation of attention
deficit post-APT treatment, however, four of those studies (Boman, Lindstedt,
Hemmingsson, & Bartfai, 2004; Insalaco; 2009; Kurtz et al., 2001; Palmese &
Raskin, 2000), included a combined treatment thus confounding the attribution for
the agent of change.
There were a range of different outcome measures utilised across the
studies. Of the four studies that used a Continuous Performance Test as an
outcome measure (Butler & Copeland, 2002; Kurtz et al., 2001; Lopez-Luengo &
Vaaquez, 2003; Sohlberg, McLaughlin, Pavese, Heidrich, & Posner, 2000), three
found an improvement on that measure following APT intervention. A
60
neuropsychological measure common to five of the studies was the Paced
Auditory Serial Addition Test (PASAT; Gronwall, 1977), with improvement on
this measure post-APT achieved in all five studies. However, despite this
commonality, two of the studies (Park et al., 1999; Sohlberg et al., 2000),
included control groups who also demonstrated an improved score on the PASAT,
suggesting that it was not APT that caused the change. Another outcome measure
common to three studies was the Test of Everyday Attention (TEA). The
participants in each of the studies suffered from mild aphasia and improvement on
all three studies was recorded for four to seven subtests of the TEA.
Different outcomes were achieved by the participants with schizophrenia in
the two respective studies. There was no significant improved attention for
participants in the Lopez- Luengo and Vazquez (2003) study, however, in the
Kurtz et al. study (2001) significant improvement was achieved for divided
attention and sustained visual attention. In two studies (Coelho, 2005; Sinotte &
Coelho, 2007) the participants with mild reading impairment showed an
improvement of language proficiency without the benefit of language intervention
suggesting that improved attention abilities may facilitate language processes in
general.
To summarise, there is growing evidence that decreased attentional
capacities which frequently present as a consequence of stroke, are amenable to
intervention (Michel & Mateer, 2006). Specifically, APT has had some positive
effect on improving attention, albeit primarily in small sample trials. In a world
where the survival of stroke is on the increase, the necessity for effective
cognitive rehabilitative techniques has become more imperative. The need for
more rigorously designed trials with large samples is needed to build on current
61
research and provide more robust findings of APT. However, the RCT and CCT
investigative framework provides difficulties when working in this field of health
research and it is those issues that provide the theme for discussion in the
following sections.
62
Table 4
Studies evaluating Attention Process Training
Authors
Design and Sample
Interventions
Sohlberg and
Pre-Post
4-8 weeks APT with 7-9
Mateer (1987)
N = 4 (2= CHI, 1=
sessions
OHI, 1= with
aneurysm)
Outcome Measures
S&M hypothesised subjects
would improve on the PASAT
but not on a measure of spatial
relations because the latter
utilises other cognitive
processes
PASAT, Consonant Trigrams,
BDI
Park Proulx and
Towers (1999)
CCT
N = 46 (23=TBI,
23=Controls)
Experimental condition=40Hrs
APT
Control condition=No APT
Palmese and
Raskin (2000)
Pre-Post Multiple
Baseline Design
N = 3 MTBI
CTT, PASAT.SDMT, Stroop,
DV, R-APT
Sohlberg,
McLaughlin,
Pavese, Heidrich
and Posner
(2000)
RCT
N = 14 TBI
2 x groups using A-B
Crossover design
1hr APT per week for 10
weeks followed by 6-7 hrs
educational and applications
programme
Experimental Condition = 24
hrs APT
Control Condition = 10 hrs
Brain Injury Education
Kurtz, Moberg,
Mozley,
Swanson, Gur
and Gur (2001)
CCT
N = 6 patients with
schizophrenia
Experimental Condition = 1hr
APT 2 x per week for ≤ 4
months plus 2 months of
PROMPT
Control Condition = No
remediation treatment
Digit Span (F & B), Stroop,
Cancellation Tests, CPT, ACT
Butler and
Copeland ( 2002)
CCT
N = 31 children with an
attentional deficit
following a treatment
and/or cancer that was
CNS related.
Experimental condition (CRP)
=21 completed 50 hrs
cognitive remediation
programme included
APT/Special education/CBT
techniques over 6 months.
Control condition (CS)=10
WISC-111 Digit Span subtest,
WRAML Sentence Memory
subtest, CPT , WRAT-111
Arithmetic subtest
TMT, PASAT, COWAT,
CPT, Stroop, Gordon
Diagnostic, Covert Orienting,
Sternberg Questionnaires,
Structured Interviews
Conclusions
All subjects showed an improvement on
PASAT but not on a measure of spatial
relations.
Exp group improved on both
neuropsychological measures. Control group
improved on PASAT only suggesting APT
results in learning of new skills rather than
improved processing. No change in BDI
scores for both groups.
All individuals demonstrated improvement
on CTT, PASAT and SDMT but the changes
may not be specific to the APT-11
Programme
Overall, there was improvement in
performances on neuropsychological
measures for both conditions. Specific
improvement for PASAT, Stroop, Trails, and
Memory for locations was greater for APT
than BIE
2/3 patients in A condition improved
significantly on tasks of divided attention
(ACT) and 2/3 on sustained visual attention
(CPT) tasks. The control group did not
improve on any tests for which data was
available (Digit Span, COT & cancellation
tests)
CRP group significantly improved on Digit
Span, Sentence Memory and the CPT. No
significant changes made by the control
group.
63
Lopez-Luengo
and Vaaquez
(2003)
RCT
N = 24 Schizophrenia
patients
Experimental Condition=13
patients received APT
Control condition = 11 patients
received standard care
Boman, Lindstet,
Hermingsson and
Barfai (2004)
Pre-Post follow-up
Design
N = 10 (5= stroke,
2=SH, 2= Encephalitis,
1= TBI
All >9 months postinjury
Single subject multiple
baseline ABA design
N = 1 patient with mild
conduction aphasia
9hrs APT per week for 3
weeks plus generalisation for
training and teaching of
compensatory strategies for
self-selected tasks
Murray, Keeton
and Karcher
(2006)
Pero, Incoccia,
Caracciolo,
Zoccolotti and
Formisano
(2006)
Sinotte and
Coelho (2007)
Insalaco (2009)
CPT, PASAT, CVLT, WCST,
TMT A&B, a dichotic
listening task , a dual dichotic
listening and a cancellation
task. Everyday Attention
Questionnaire
Post performance on APT,
Digit Span, RBMT, ClaesonDahl Memory test, AMPS,
EBIQ
No significant improvement of attention
found as a result of APT although treatment
group demonstrated improvement in
executive functions as measured by WCST.
17hrs APT-ІІ and 20hrs of
APT-11 home practice
ADP, TLC-E, CETI, Logical
memory and Digit Span, TEA,
APT-11 questionnaire
Pre-Post
N = 2 patients with
severe TBI >1 yr posttrauma
85 sessions APT
TAP, TEA
Pre-Post
N = 2 (1 with CVA 6
months post-onset with
mild reading
impairment, 1 control
with no neurological
history)
Pre-Post follow up
multiple Baseline
Design
N = 6 with ADHD and
ED
16 sessions of APT-ІІ over 5
weeks
WAB-AQ, GORT-4, TEA,
APT-ІІ questionnaire,
Reading Rate
Higher raw scores achieved on Digit Span
but not significant. Higher scaled score
achieved on seven TEA subtests with
significant change on two subtests measuring
sustained selective and divided attention.
Minimal changes on APT questionnaire
Both patients improved on measures of
selective attention. The patient with pretreatment vigilance and divided attention
deficits demonstrated improvement in both
these areas.
Improvement on WAB-AQ and GORT-4
although not clinically significant.
Significant improvement on seven subtests
of TEA. Improved rating on APT-ІІ
questionnaire
13 weeks APT-ІІ and GPDR
training
WMS-111, CTT, DVT,
BRIEF-A, Attention
Questionnaire from APT-11
Improvement on more complex tasks of
attention. No change on Digit Span score.
3/6 reduced the APT questionnaire raw
score. APT with GPDR appears helpful in
reducing attention problems in adults with
ADHD and ED
64
ACT=Auditory Consonant Trigrams, ADHD=Attention Deficit Hyperactive Disorder, ADP=Aphasia Diagnostic Profiles, AMPS=The Assessment of Motor
and Processing Skills, APT=Attention Process Training, BDI=Beck Depression Inventory, BIE=Brain Injury Education, CCT=Clinical Control Trial,
CETI=The communicative effectiveness index, CHI=Closed Head Injury, COWAT=Controlled Oral Word Association Test, CPT=Continued Performance
Test, CRP=Cognitive Remediation Programme, CS=Comparison subjects, CTT=Consonant Trigrams, CVA=Cerebrovascular Accident, CVLT=California
Verbal Learning Test, DV=Digit Vigilance, EBIQ=The European Brain Injury Questionnaire, ED=Executive Dysfunction, GORT-4=Gray Oral Reading Tests4, GPDR=Goal, Plan, Do, Review, MTBI=Mild Traumatic Brain Injury, OHI=Open head Injury, TBI= Traumatic Brain Injury, PASAT-Paced Auditory Serial
Attention Task, PROMPT=Prospective Memory Training, R-APT=Revised Auditory Processing Test, RBMT=Rivermead Behavioural Memory Test,
RCT=Randomised Control Trial, SDMT=Symbol Digit Modalities Test, SH=Subarachnoid Haemorrhage, SSD=Single Subject Design, TAP=Test for
Attentional Performance, TBI=Traumatic Brain Injury, TEA=Test of Everyday Attention, TLC-E=Test of Language Competence-Expanded Version,
TMT=Trail Making Test, WAB-AQ=Western Aphasia Battery-Aphasia Quotient, WAIS-R=Wechsler Adult Intelligence Test-Revised, WCST=Wisconsin Card
Sorting Test, WISC 111=Wechsler Intelligence Scale for Children-Third Edition, WMS-111=Wechsler Memory Scale-Third Edition, WRAML=Wide Range
Assessment of Memory and Learning, WRAT=Wide Range Achievement Test-Third Revision.
65
Barriers to Trials in Cognitive Rehabilitation
Non-medical research (i.e. non-pharmaceutical and non-surgical research)
endeavours to conduct first class research, however, the RCT design has several
limitations and inherent problems when applied outside this context. Some behaviour
researchers criticise the RCT as being too concerned with theory and the remediation
of impairment with little focus on reducing disability and restoring social functioning
(Bottomley, 1997; Hart, Fann, & Novack, 2008; Pringle & Churchhill, 1995; Roth &
Fonagy, 2005; Stephenson & Imrie, 1998). Unlike pharmaceutical or surgical trials,
standardization of the content and delivery of behavioural interventions, such as
cognitive rehabilitation, is more complex and therefore presents major challenges to
investigators. The treatment under investigation is more likely to be influenced by
unknown factors which may affect the scientific reliability of measured outcomes
(Hart et al., 2008). „Extraneous variable‟ is a general term sometimes used to refer to
any variable other than the treatment which might have an effect on the outcomes of
interest (Bordens & Abbott, 2002; Isaac & Michael, 1981). Non-specific features of
the treatment such as time spent with participants, number of contacts, timing of
intervention, or length of follow-up, are examples of extraneous variables and need to
be comparable in all conditions so that the mechanistic effects of the experimental
intervention, rather than instructor or research-team attention and social support, will
be credited for differences in outcomes (Borderns & Abbott, 2002). Non-medical
research design requires rigorous procedures to eliminate the influence of such
variables. It is argued that rigorous systemised randomising should evenly balance
out such factors (Togerson & Togerson, 2001), however, this assumption is only true
when trials are large enough for this balancing to take place (Roth, Fonagy, Parry,
Target, & Woods, 2005).
66
An additional difficulty lies in defining the characteristics of the sample and
achieving adequate sample sizes. While large samples are required in order to have
sufficient power to detect treatment effects (Aveline, Shapiro, Parry, & Freeman,
1995) in stroke populations, it is often the case that the larger the sample the more
heterogenous its characteristics. Stroke patients present with different types of stroke
(e.g. ischaemic stroke, haemorrhagic stroke and subarachnoid haemorrhage) with an
extensive array of corresponding problems. This makes it less likely that everyone
receiving the treatment will benefit and will therefore reduce the likelihood of finding
significant treatment effects. Thus, there is a need to define samples a priori in such a
way as to ensure confidence in the conclusions drawn from the data, but not be as
restrictive as to reduce your likelihood of obtaining your required sample size (Schulz
& Grimes, 2005). This must include the need to define time post-injury and exclude
or balance for confounds such as stroke severity, while ensuring a sample that is
diverse enough to be representative but with reasonable expectation that treatment
will be beneficial. This should also include a definition of how those individuals who
are likely to benefit from the treatment will be defined with regard to the problem
being treated. For example, in defining the minimal level of deficit on an assessment
of attention that would be considered sufficient to require treatment, one must
consider not only the psychometric properties of the assessment tool and its
appropriateness to the population of interest, but also the ease with which the
assessment could be integrated into existing clinical settings (Meinert & Tonascia,
1986).
It is commonly agreed that non-medical research is expensive to conduct
because recruitment usually requires large samples in order to ensure any observed
differences are due to the intervention. In addition, those administering the
67
intervention are either professionals with expertise in that particular field of
investigation or are researchers who require extensive training and monitoring, both
of which can be expensive (Bottomley, 1997). Reimbursement provided to
physicians for their role in clinical trials often falls far short of their costs, which may
include the hiring of additional nursing and data management staff to ensure that
patients fully understand the risks and benefits of participation, to track participating
patients and collect and report the necessary data.
An additional problem with non-medical research, such as is the case for
cognitive rehabilitation, is that double blinding is not possible and effective blinding
of the participant is only rarely achievable (Rains & Penzien, 2005). Therefore, there
is a need to put greater emphasis on ensuring systems are in place to guarantee
blinding of the individual conducting baseline and outcome assessments. Extensive
effort by the researchers is required to ensure appropriate recruitment and
randomisation so as to reduce the risk of bias. However, randomisation in nonmedical studies, where it is often difficult to blind participants to group allocation,
can affect levels of motivation in potential participants. Excluding choice by
allocating patients randomly to one or other treatment is seen as a great strength in
clinical trials, yet in behavioural trials this has brought criticism (Bottomley, 1997;
Pringle & Churchill, 1995). Choosing your preferred intervention, it is argued,
increases motivation. If this is so, then it must be established if those motivational
factors affect the efficacy of an intervention and if so, how motivation can best be
measured.
A final challenge in conducting non-medical research relates to its potential to
interfere with existing practises. Health professionals already have demanding
workloads, and can become de-motivated toward the research when established
68
schedules are disrupted, particularly if immediate patient benefit is not obvious.
Research methodology should adapt to existing routines as much as practicable, not
only to maintain effective relationships with hospital staff but also to ensure
continuity in the delivery of health care (Bottomley, 1997; Pringle & Churchill,
1995).
Appropriateness of Control Conditions
The control group is not exposed to the experimental treatment and provides a
baseline measure which gives investigators important clues to the effectiveness of the
treatment, its side effects, and the parameters that modify those effects. The absence
of a control group raises concerns that any observed improvement post-training arises
as a function of practice on the outcome measures or due to some extraneous factor.
When conducting research for neuropsychological rehabilitation different control
conditions present complex risk-benefit ratios that need close consideration before
decisions are made for the design of the research (Saks, Jeste, Granholm, Palmer, &
Schneiderman, 2002).
The no-treatment control group is deemed to be the easiest and most cost
effective to run. This condition provides control for the effects of spontaneous
recovery, regression to the mean and the effects of repeated testing on outcome
measures which is particularly crucial in studies of cognitive remediation (Park &
Ingles, 2001). However, considerable ethical objections have been raised about
denying interventions that are believed or assumed to be beneficial, to a group who is
defined as having a particular problem (Saks et al., 2002).
Another disadvantage is that high drop-out rates may more likely be under a notreatment group condition. In response to the ethical concerns, many clinical studies
do not include a non-treatment group but rather, when available, utilise existing
69
standard-care therapy thereby assuring participants do not go untreated for their
condition. As well as overcoming the problem of denying treatment, standard care
often provides a simple, clean, and cheap control condition. The disadvantages of
standard care include possible high variability in care, the lack of effectiveness if
standard care is minimal or not accessible and the potential for spill-over of the
intervention into the standard care groups.
Wait-list control groups receive the treatment after the treatment period for the
experimental group and the waiting time is typically the same duration as the
treatment period. The wait-list design condition controls for the effects of time and
regression to the mean (Hart et al., 2008). However, there are disadvantages to using
this form of control group design. Wait-list control groups are not appropriate for
protracted time periods as it raises the ethical dilemma of withholding treatment.
This design is not suitable for those patients who are in the acute stages of their
illness as the wait period introduces possible extraneous variables, such as
spontaneous recovery, that may not be measureable but may impact on outcomes.
The waiting period also increases the probability of higher attrition and is likely to
worsen over time (Byrne, Fursland, Allen, & Watson, 2011). Furthermore, the waitlist group must undergo two rounds of pre-assessment, thus introducing practise
effects as a possible confounding factor in the performance of participants on those
measures.
The true placebo condition, as employed in pharmaceutical trials, is virtually
impossible to achieve in non-medical research given that double blinding is
impossible. Single blinding is also elusive since most participants are able to discern
whether they are in the “more active” or “less active” treatment group, so reducing
their expectation of improvement and thus the integrity of the placebo effect
70
(Whitehead, 2004). Alternative care or sham treatments can be defined as one
performed on a control group participant to ensure that he or she experiences the same
incidental effects as the experimental group. In non-medical research this control
condition can be problematic if both groups improve, as the ability to determine real
treatment effects is less discernible. Again ethical opposition to alternative treatment
groups include the withholding of effective treatment, providing irrelevant treatment,
possible risk to the participant and the inherent nature of misleading the participant
assigned to the alternative treatment (Rothman & Michels, 1994).
A further concern that can arise with randomisation is that some individuals
may consent to participation in the study, however, with the steadfast hope that they
will be randomised into the treatment group particularly if they perceive the treatment
on offer as beneficial to their recovery. If this fails to eventuate, dropout rates may
increase due to disappointment and frustration (Karlawish & Whitehouse, 1998). A
well-conceived control condition can include an alternative activity of value that is
unrelated to the desired outcomes of the trial and that is attractive to prospective
participants. Burdening participants with time-consuming and worthless tasks is not
appropriate.
The problems associated with RCTs for studying the efficacy of cognitive
interventions must be balanced against the benefits that this type of design provides,
(i.e., the most rigorous and robust means of identifying cause and effect). Some of
the difficulties identified could be resolved if sufficient funding was available, so in
line with current knowledge and demands, government and private funding agencies
need to prioritise support for this type of research. Multi-centre approaches may be
one solution to reducing the high costs of conducting non-medical research. Not only
would financial and staff costs be distributed across settings, the problem of having to
71
recruit large sample sizes would also be divided between sites. Data from each site
would be collated for analysis.
In summary, the world-wide trend for the incidence of stroke is on the increase,
as is the number of people surviving stroke. A significant number of stroke survivors
have been identified as experiencing post-stroke cognitive deficits with impairment of
attention being a common factor. To date, there have been very few studies
investigating neuropsychological rehabilitation for people with attention deficits poststroke. Reasons behind the shortage of such research may lie in the difficulties
inherent with randomised control trials when conducting non-medical research such
as ethical considerations and available resources. The increasing demand for
cognitive rehabilitation for this population necessitates further well-designed research
in this area with outcomes measured on both tests of attention and functional abilities.
The purpose of the current study is to add to a developing and evolving
knowledge base on cognitive rehabilitation post-stroke. In order to obtain the highest
level of evidence the study design is that of a randomised control trial. Those
problems previously discussed in this chapter that may arise when a RCT design is
used for behavioural interventions were addressed and either minimised or eliminated
altogether. For example, sample size, the make-up of the sample, the inclusion of
rigorous systemised randomising, the inclusion of health-related quality of life
measures as well as the use of conventional cognitive measures, and ensuring
stringent standardisation of the content and delivery of the intervention, were all
measures taken to ensure confidence in the findings.
The primary aim of this study was to investigate the impact of Attention
Process Training on attention deficit in patients at the post-acute stage of stroke
(between 5 to 9 weeks after the occurrence of the stroke). The impact, if any, of APT
72
on health-related quality of life was also of interest as was investigating whether the
neuropsychological profile of stroke patients had any impact on attention process
training. Finally, the study attempted to look at any change in the clinical profile of
stroke patients that might occur as a result of APT.
73
Chapter 4: Methods
The Stroke Attention Rehabilitation Trial (START) was a Health Research
Council of New Zealand funded project. This PhD thesis focuses on an aspect of the
START project (i.e. the impact of APT on attention in stroke survivors at five to nine
weeks
post-stroke). I was a member of the operations committee which was
responsible for the execution and management of the study. Initially, the committee
convened weekly, then fortnightly for the six months leading up to the
commencement of data collection. I was also employed full-time on the study for
two years and responsible for the recruitment of the participants and the
administration of the APT programme.
Ethics
Approval for the conduct of this study was obtained from the Northern X
Regional Health and Disability Ethics Committees Ref (NTX/06/10/124). This study
is registered with the Australian Clinical Trials Register (CTRN12607000045415).
The research was run according to New Zealand Good Clinical Research Practice
Guidelines. Ethics for this study was also granted by the Department of Psychology
Research and Ethics Committee at the University of Waikato (No. 08:07).
Participants
Participants included all survivors of ischemic stroke or primary intracerebral
haemorrhage consecutively admitted to inpatient neurological rehabilitation units of
Middlemore and North Shore Hospitals over an 18 month period. Stroke diagnosis
was according to the standard WHO criteria which describe a stroke as an
interruption of the blood supply to the brain causing damage to the brain tissue (Aho
et al., 1980).
74
Patients were required to meet certain eligibility criteria for inclusion in the
study. The participant must have had a first-ever confirmed stroke which must have
occurred in the previous 30 days. The participant must also have given informed
consent, and must have been comfortable having a conversation in English (as
standardised administration of tests requires English fluency). The participant must
have obtained a score ≥20 on the Mini Mental State Exam and finally, the participant
must have been signed off by their medical officer as being medically stable to
complete APT training.
Potential participants were excluded from the study if they had a psychiatric
illness and/or were on psychotropic medications which in the opinion of a clinician
would have had a significant effect on attention processing. Exclusion also applied if
the participant had been informed that the amount of alcohol they consumed was a
problem or there was a record in the medical notes of a person having alcoholism.
Other exclusion criteria included the participant being involved in another study that,
in the opinion of the investigator, may have affected cognitive performance or added
significantly to participant burden or if the participant had a contraindication to
Attention Process Training such as blindness, deafness, or an inability to talk.
If the patient passed the initial screening, they were administered the attention
tests to ascertain the presence of an attention deficit. This was determined by a score
of one standard deviation below the normative mean scores on any one test reflective
of attention (i.e., Integrated Visual and Auditory Continuous Performance Test [IVACPT] Attention Quotient score, Trail Making Test Part A and B, the Bells
Cancellation Test, and the Paced Auditory Serial Addition Test). These measures
were selected because they provide a measure of the four components of attention
75
that are addressed by APT and because they provide measures for both auditory and
visual modalities of attention.
Of the 334 patients initially approached, 107 gave informed consent however
only 95 patients were found to meet the eligibility criteria. (Refer to Figure 5 for the
number of participants at each stage of the study). Two the 12 who did not meet the
eligibility criteria did not have confirmed stroke diagnoses, three had a MMSE <20,
three were not medically stable, one was less than four weeks post-stroke, one was in
a competing study and two withdrew their interest.
First-ever Stroke
patients approached
N = 334
Consent/Eligibility/Initial Screen
MMSE/Barthel.Demographics
N = 107
Baseline Attention Screen
N = 95
Patients with Deficit N = 84
Neuropsychological Baseline
Assessment/HRQoL
Not eligible
N = 12
No Deficit
N = 11
6 withdrew from
study
Randomised
N = 78
Allocated 30 Hours
APT
N = 35
Allocated to
Standard Care
N = 43
Post Intervention follow-up
N = 68
Figure 5. Study Design and recruitment
10 were lost to
follow-up
76
Eighty four participants were then found to have an attention deficit while 11
did not. Five patients then withdrew from the study and one other moved away from
the area leaving 78 patients to be randomised. Thirty five patients were randomised
into the APT group and 43 were randomised into the Standard Care group. (See
Figure 5).
The ethnic composition of the APT intervention group was; 80% European, 5.7
% Maori, 11.4% Pacific Islander, and 2.9 % Indian. Sixty percent of the APT group
were male, 40% were female and the range of ages was from 24-94 years with a mean
age of 69.54 years. The Standard Care group was made up of 76.7% European,
16.3% Maori, and 7% Pacific Islander and there were 60.5% male and 39.5% female.
The ages ranged from 38 to 85 years with a mean age was 68.51 years.
Design
Study Overview.
The staff of the inpatient Acute Treatment and Rehabilitation wards and the
acute stroke wards of Middlemore Hospital and North Shore Hospital were informed
of the study by means of a presentation at their weekly in-service meeting. Senior
stroke consultants, some of whom were part of the steering committee for the START
project, ward clerks, stroke nurse specialists and staff of a community based
rehabilitation team were key referrers of potential participants. Those patients who
consented to participate in the study and met the eligibility criteria were assessed to
determine whether or not they had an attention deficit. If they did have an attention
deficit, they were administered the Barthel Index as well as all other
neuropsychological measures and all health related quality of life measures. The data
from these measures were used as baseline measures however for the purposes of this
77
study, only the attention measures and the SF-36 were re-administered at four-five
weeks post-randomisation. All other measures were re-administered at six months
post stroke as part of the START project (Barker-Collo, et al., 2009). (Refer to Table
5 for Schedule of assessments).
Table 5
Schedule of Assessments
Measure
Screening
Inclusion
MMSE
√
Attention Screen
IVA-CPT
Bells
Trails A/B
PASAT
√
√
√
√
Randomisation
Barthel Index
√
Additional
Neuropsychological
Tests
Stroop
CVLT-11
LM
VPA
ROCF
BNT
COWAT
Baseline
5 Weeks
6 months
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
SF-36
√
√
√
CFQ
√
√
mRS
√
√
GHQ
√
√
BNT = Boston Naming Test, CFQ, Cognitive Failures Questionnaire, COWAT = Controlled Oral Word
Association Test, CVLT = California Verbal learning Test, CHQ = General Health Questionnaire,
HRQoL = Health Related Quality of Life, IVA-CPT = Integrated Visual and Auditory Continuous
Performance Test, LM = Logical Memory, MMSE = Mini Mental State Exam, mRS = Modified
Rankin Scale, PASAT = Paced Auditory Serial Addition Test, ROCF = Rey Osterreith Complex Figure,
SF-36 = Short Form 36, VPA = Visual Paired Associates.
HRQoL
Apparatus and Measures
Eligibility Measure.
Mini Mental State Exam (MMSE) Folstein, Folstein & McHugh, (1975).
The MMSE is a brief objective assessment (administration time is
approximately 10 minutes), that can be used to indicate the presence of cognitive
impairment. It is employed extensively in clinical studies, community surveys and
epidemiological studies (Tombaugh, McDowell, Kristjansson, & Hubley, 1996). It
78
was used in this study to screen for eligible participants who must have obtained ≥20
in order to qualify for inclusion.
Reliability coefficients for the MMSE are moderate to high and there is high
sensitivity for cognitive decline in dementia and head injury. Test-retest reliability
was .89 and a combination of test/retest and inter-rater reliability was .82 (Folstein,
Folstein, & McHugh, 1975). A correlation coefficient of .78 has been found with the
Wechsler Adult Intelligence Scale for Verbal Intelligence Quotient and .66 for
Performance Intelligence Quotient (Burns, Lawlor, & Craig, 2004).
The MMSE is an 11 question measure that tests five areas of cognitive function
including orientation, registration (immediate memory), attention and calculation,
recall, and language. The maximum score that can be achieved on this measure is 30
Baseline Measures.
Barthel Index (Mahoney & Barthel, 1965).
The Barthel Index has become one of the most widely used tools to measure a
person‟s ability in activities of daily living. It was developed to assess the severity of
disability or independence in personal care and mobility in stroke patients. It is easily
administered requiring 2 to 10 minutes to complete. Shah, Vanclay and Cooper
(1989) report an alpha internal consistency coefficient of 0.87 to 0.92. The scale
consists of 10 variables that are related to activities of self-care (feeding, grooming,
bathing, dressing, bowel and bladder care, and toilet use) and mobility (ambulation,
transfers, and stair climbing). Scoring of this measure is also easy with scores of 020 indicating total dependence; 21-60 severe dependence; 61-90 moderate
dependence and 91-99 slight dependence (Granger, Sherwood, & Greer, 1977;
Granger, Albrecht, & Hamilton, 1979; Sulter, Steen, & De Keyser, 1999). For the
79
purposes of randomisation participants were grouped into two groups, those who
obtained scores of ≥ 18 or <18.
Neuropsychological Measures.
The neuropsychological tests used in this study are well validated and
commonly used in stroke samples (Spreen & Strauss, 1998). Procedure for
administration of all neuropsychological tests was conducted in accordance with
respective manuals or published standard procedures. Except for the Bells
Cancellation Test, raw scores on all tests were converted to z-scores and compared to
normative data. Normative data for The Trail Making Test Part A & B, the Paced
Auditory Serial Addition Task, The Victorian Stroop Test and the Controlled Oral
Word Association Test were obtained from A Compendium of Neuropsychological
Tests (Spreen & Strauss, 1998). Normative data for the IVA-CPT, the Wechsler Adult
Intelligence Scale-III, the Wechsler Memory Scale-III, the California Verbal Learning
Test and the Boston Naming Test were obtained from the respective test manuals. If
normative data was not available for older adults, data from the Mayo‟s Older
Americans Normative Studies (MOANS) was used (Steinberg, Bieliauskas, Smith, &
Ivnik, 2005; Steinberg, Bieliauskas, Smith, Langellotti, & Ivnik, 2005; Steinberg,
Bieliauskas, Smith, Ivnik, & Malec, 2005).
Attention.
The attention measures that were selected for this study addressed all four
components of attention targeted in APT. The IVA-CPT was used to obtain a measure
of sustained and selective attention, the Trail Making Test was used to measure
sustained and alternating attention, the PASAT was used to measure sustained and
divided attention and the Bells Test was used to measure sustained and selective
attention in the visual modality. Initially, the scores obtained on measures of attention
80
were used as a screening tool to identify an attention deficit. An attention deficit was
identified as present if participants scored below one standard deviation below the
normative mean on any one of the following measures; the auditory quotient or visual
quotient of the IVA-CPT, the PASAT or either trial of the Trail Making Test, or if they
made > 3 errors on the left or right side of The Bells Test. The scores obtained on all
attention measures for those participants who were identified as having an attention
deficit, were also used as the baseline measures.
The Integrated Visual Auditory- Continuous Performance Task (IVA-CPT)
(Sandford & Turner, 2000).
The IVA-CPT is an easy to administer computerised continuous performance
test that is designed to assess two major factors. The Full Scale Attention Quotient
(FSAQ) is a measure of problems of inattention, loss of focus, and slow processing
speed. The Full Scale Response Quotient is a global composite score reflecting
problems of response inhibition (i.e. impulsivity), sustaining effort, and making
consistent responses. Seckler et al. (1995) reported 1 to 4 week test-retest reliability
coefficients ranging from .37 to .75 which they concluded were very small practise
effects. It was concluded that “any observed effects of 15 quotient points (i.e. one
standard deviation) or more are interpreted as not likely to be due to random
fluctuations” (Sandford & Turner, 2000, p.19; Thickpenny-Davis, Barker-Collo, &
Caplan, 2007, p. 306). Of the 22 scale raw scores produced on this test, 20 scales had
significant positive relationships with 18 of the 20 showing a moderately strong to
very strong relationship (.46 to .88; Seckler, Burns, Montgomery, & Sandford, 1995).
The following are guidelines for the description of observed changes in quotients:
<15 = No Significant Change; 15 to 22 = Mild Change; 23 to 29 = Mild to Moderate
81
Change; 30 to 37 = Moderate Change; 38 to 44 = Moderate to Marked Change; and
45+ = Marked Change (Sandford & Turner, 2000).
Administration.
Test instructions are presented visually on the computer screen using a clear
female voice. Like all good continuous performance tasks the IVA-CPT is designed
to be mildly boring and therefore demanding of sustained attention, with a poor
performance producing errors of inattention (omission) and impulsivity
(commission). It also provides an objective measure of fine motor regulation and
speed. On this task the individual was required to press a mouse button in response
to an auditory or visual target stimulus (number 1) that appeared or was heard via a
computer and to refrain from pressing the mouse button when a non-target stimulus
(number 2) was presented. A one and a half minute warm-up session for both the
auditory and visual stimuli was given, with only the number 1 presented as stimuli,
which provided an opportunity for those participants who had not worked on a
computer before, to become familiar with the use of the mouse. This was followed
by a 32 item practice session using both numbers 1 and 2. The computer provided
corrective feedback to the participant when errors were made. As well as allowing
for minimising of practise effects, the practise session also provided the examiner
with the opportunity to determine whether the participant understood the task. If the
participant appeared uncertain of what was required on this task further instruction
was provided until full comprehension was achieved. The test itself took about 13
minutes and involved the participant responding to or inhibiting a response over five
sets of 100 stimulus presentations. The visual “1”s and „2‟s were presented for 167
milliseconds, and the verbal “1”s and “2”s were presented for 500 milliseconds. The
main test collected a measure of impulsivity by creating a response set of not
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responding; 84% of the stimuli or 42 out of the first 50 „frequent‟ block of trials were
“1”s intermixed with eight “2”s. During the second „rare‟ block of 50 trials, many
“2”s (84% of stimuli) were presented and few “1”s, and the examinee was forced to
wait to make his or her responses every six to nine seconds when a “1” was heard or
seen. This second block of trials “pulls” for inattention, and creates a response set of
responding. An equal number of auditory and visual stimuli were presented in a fixed
pattern in each block, with the patterns of “1”s and “2”s during the frequent and rare
blocks being mirror images of each other. The computer automatically saved the
performance scores for later analysis.
Scoring.
The primary diagnostic scales are the Full Scale Attention Quotient and the Full
Scale Response Control Quotient.
The global Full Scale Attention Quotient consists of three separate Auditory and
Visual Attention quotients made up of three scales. They are:
1.
Vigilance: measures errors of omission, providing an indication of problems
related to inattention. Vigilance is related to failure to respond to a target during rare
blocks. A low Vigilance score may indicate problems with staying on task, being
alert, negligence or indifference. A high score may indicate attentive and alert
responding.
2.
Focus: “reflects the total variability of the speed of mental processing for all
correct responses and thus, is designed to be sensitive to an unusual number of
occurrences of slow reaction times” (Sandford & Turner, 2000, p. 2).
3.
Speed: “the reaction time of all correct responses throughout the test and helps
identify attention processing problems related to slow mental processing” (Sandford
& Turner, 2000, p. 2).
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The Full Scale Response Quotient consists of three response control primary
scales for both visual and auditory modalities. They are:
1.
Prudence: measures errors of commission - reflecting poor response inhibition
problems and impulsivity. It is a measure of “the ability to stop, think and not
automatically react to a foil” (Sandford & Turner, 2000, p. 8). Low prudence scores
indicate thoughtlessness, carelessness or over-reactivity. High scores indicate
mindful, cautious, careful and circumspective responding. For the purposes of this
study, the data from the Prudence (auditory and visual) scale were presented as
quotients to provide information on whether APT improved impulsivity.
2.
Consistency: the variability and reliability of response times and “is used to
help measure the ability to stay on task” (Sandford & Turner, 2000, p. 2).
3.
Stamina: identifies any difficulty with sustained attention and effort over time,
and with maintaining speed of mental processing. This score is calculated through
comparing the mean reaction times of correct responses during the first 200 trials to
those of the last 200 trials.
In addition, the IVA-CPT has three validity scales (Sandford & Turner, 2000).
First, the Persistence scale compares simple reaction times before and after the test.
Reductions in reaction time may be indicative of: a lack of motivation when the
examinee is asked to do „one more thing‟; an oppositional attitude; or a reflection of
mental or motor fatigue (Sandford & Turner, 2000). Second is the Sensory/Motor
scale which is used to “rule out possible unusual neurological, psychological or
learning problems evidenced by slow simple reaction time when only the target “1” is
presented” (Sandford, 2000, p. 7). Finally, the Comprehension scale indicates the
likelihood of random responding (Sandford & Turner, 2000).
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All IVA-CPT scores are presented both as raw scores and quotient scores, with
the quotient scores having a mean of 100 and a standard deviation of 15. The
normative database (N=781) for the IVA-CPT is broken into the following age
groups: 5-6, 7-8, 9-10, 11-13, 14-17, 18-24, 25-34, 35-44, 45-54, 55+ years; and is
also divided by gender; with each gender/age group being sufficiently large for valid
clinical interpretation (Sandford & Turner 2000). All of the individuals in the
database reported having no learning, attention, neurological, or psychological
problems. For each of the IVA-CPT global scales, attention scales, response control
scales and the Sensory/Motor scale, it is proposed that an individual score of less than
90 can be labelled Mildly Impaired; less than 80 is Moderately Impaired; less than
70, Severely Impaired; and less than 60, Extremely Impaired.
In addition, the IVA-CPT has three validity scales (Sandford & Turner, 2000).
First, the Persistence scale provides a comparison of simple reaction times before and
after the test. Reductions in reaction time may be indicative of: a lack of motivation
when the examinee is asked to do „one more thing‟; an oppositional attitude; or a
reflection of mental or motor fatigue (Sandford & Turner, 2000). Second is the
Sensory/Motor scale which is used to “rule out possible unusual neurological,
psychological or learning problems evidenced by slow simple reaction time when
only the target “1” is presented” (Sandford & Turner, 2000, p. 7). Finally, the
Comprehension scale indicates the likelihood of random responding (Sandford &
Turner, 2000).
However, for the purposes of this study only the measures of interest were used:
The Full Scale Attention Quotient, the Auditory Attention Quotient, the Visual
Attention Quotient, the Full Scale Response Quotient, the Auditory Prudence
Quotient and the Visual Prudence Quotient.
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Paced Auditory Serial Addition Test (PASAT) (Gronwall, 1977).
The PASAT is a serial addition task used to assess rate of information
processing (Gronwall & Wrightson, 1981), sustained attention (Cohen, SparlingCohen, & O‟Donnell, 1993), and divided attention (Lezak, 1995; Lezak et al., 2004;
Ponsford & Kinsella 1992; van Zomeren & Brouwer, 1994). It is one of the most
frequently used measures of attention in patients with mild traumatic brain injury
(Cicerone, 1997; Gordon & Zilmer, 1997; O‟Jile et al., 2006; Sohlberg & Mateer,
1989; Tombaugh, 2006; Vanderploeg, Curtiss, & Belanger, 2005).
The PASAT has been a primary outcome measure in a number of efficacy
studies of APT (Palmese & Raskin, 2000; Park et al., 1999; Sohlberg & Mateer, 1987;
Sohlberg et al., 2000). (See Table 4 Studies evaluating Attention Process Training).
It is also used as a neuropsychological measure in clinical settings with patients
suffering from a wide variety of neuropsychological syndromes including
degenerative disorders, Parkinson„s Disease (Dujardin et al., 2007), Huntington‟s
Disease, Vascular Cognitive Impairment, Korsakoff‟s Syndrome, and Multiple
Sclerosis (Lezak, 1995). Indeed, the PASAT is included as a core measure in the
Multiple Sclerosis Functional Composite (MSFC), a quality-of-life outcome measure
in Multiple Sclerosis-related clinical trials (Barker-Collo, 2005; Nagels et al., 2005;
Rudick et al., 1997).
Egan (1988) and Johnson, Roethig-Johnson, and Middleton (1988), found splithalf reliability for the PASAT to be high (.9) and MacLeod and Prior (1996), found
performance across different pacings was also highly correlated. Test-retest
correlations of this test after 7 to 10 days is high (>.9) (McCaffrey et al., 1995)
however practice effects on this task are significant although minimal after the second
presentation (Gronwall, 1977; Tombaugh, 2006).
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The PASAT was selected for use in this study because although it can be a
difficult and stressful test, it is nevertheless useful for the detection of subtle attention
deficits (Lezak et al., 2004). Furthermore, it provides another index of auditory
attention beside the IVA-CPT.
Administration.
For this task, sixty one numbers ranging from 1 to 9 were presented to the
participant with the use of a tape recorder. The participant was required to add each
number to the number that immediately preceded it. For example if the digit 6, 3, and
2 were presented, the participant would respond with the correct answers 9 and 5.
The pace at which the numbers are presented can vary at 1.2, 1.6, 2.0 or 2.4 seconds
apart. In this study only the two slowest trials (2.0 and 2.4 seconds) were
administered as they were considered to be appropriate paces for stroke patients in the
acute stage. The participant‟s response was required prior to the presentation of the
next digit for a response to be scored as correct. In this study, the participant was
initially presented with a practice trial followed by the two test trials.
Scoring.
Scoring of the task was the total number of correct responses made with a
maximum score of 60 per trial.
The Trail Making Test A and B (TMT A & B) (Partington & Leiter, 1949).
The TMT is a paper and pencil test that requires the connection of encircled
numbers (Part A) and numbers and letters (Part B) in the proper order. It is a wellestablished test that is available in written and oral forms, the latter omitting the
visual-motor component of the task. The TMT is a test frequently used to assess
attention, visual search, scanning, speed of processing, mental flexibility and
executive functions (Spreen & Strauss 1998; Tombaugh, 2004). Part B of the TMT is
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highly sensitive to the effects of brain injury (Lezak, 1995). The TMT has also been
reported as a useful tool in identifying cognitive decline in dementia (Kowalczyk,
McDonald, Cranney, & McMahon, 2001). It is correlated highly with driving ability
and along with other measures is used for determining a person‟s driving “readiness”
following stroke (Lundqvist, Gerdle, & Ronnberg, 2000; Mazer, Korner-Bitensky, &
Sofer, 1998). The TMT has however been criticised for its use with patients who may
experience physical constraints (Lezak, 1995; Waldstein, et al., 2003).
In terms of construct validity, Part A and Part B correlate only .49 with each
other. The results of studies conducted by Gaudino, Geiser, and Squires (1995) and
Woodruff, Mendoza, Dickson, Blanchard, and Christenberry (1995), suggest that Part
B is a more difficult cognitive task than Part A as the participant is required to switch
between letters and numbers. As such Part B is a measure of alternating attention and
it is for this reason and its use as a primary outcome measure in previous studies
evaluating APT (Lopez-Luengo & Vaaquez, 2003; Sohlberg et al., 2000) that the
TMT was selected for use in this study.
Performance on the TMT is affected by age and education but not gender nor
culture (Arnold, Montgomery, Castaneda, & Longoria, 1994; Heaton, Grant, &
Matthews, 1986, as cited in Spreen & Strauss, 1998; Tombaugh, 2004). Inter-rater
reliability is excellent with coefficients of .94 for Part A and .90 for Part B having
been reported (Fals-Stewart, 1991, cited in Spreen & Strauss, 1998). Other reliability
coefficients have been reported for this test with most having been above .60, several
above .90 and most above .80 (Spreen & Strauss, 1998). The TMT has shown high
concurrent validity with the Arithmetic, Digit Span and Digit Symbol subtests of the
Wechsler-Bellevue Scale.
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Administration.
On Part A the participant, using a pencil, was required to join a series of circled
numbers (without lifting the pencil) in ascending order from 1 to 25, strategically
displayed on an A4 sheet, in as little time as possible. This provided a baseline
measure of processing speed. On Part B, a more complex task, the sheet contained
circled numbers (1 to 13) and letters (A to L) and the participant was required to join
the circles alternating between numbers and letters in ascending order (i.e., 1-A-2-B3-C etc). The participant was instructed to connect the circles as quickly as possible,
without lifting the pencil from the paper. If the participant made an error on either
Part A or Part B, it was immediately pointed out to the participant who was then
instructed to return to the last circle completed correctly in the sequence. Errors
affected the participants score in that the correction of the error was included in the
time to complete the task.
The test took on average 5 to 10 minutes to administer. Participants were urged
to perform the task as quickly as they could and performance was measured as the
time in seconds it took to complete each task. It was important to ensure that the
participant understood the instructions fully before the task began because timing
commenced immediately the pencil touched the paper.
Scoring.
Raw scores were converted to standardised scores and compared to available
normative data. (Strauss, Sherman, & Spreen, 2006).
The Bells Cancellation Test (Gauthier, De haut & Joanette, 1989).
The Bells Cancellation Test is widely used to detect visual inattention or
unilateral neglect and is appropriate for use with teenagers and adults (Azouvi et al.,
2006; Beis et al., 2004; Tant, Kuks, Kooijman, Cornelissen, & Brouwer, 2002). It has
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also been used as part of a battery of tests determining the impact of perceptual
deficits on functional autonomy in elderly patients post-stroke (Mercier, Desrosiers,
Herbert, Rochette, & Dubois, 2001). They examined the Bells Test in 59 subjects, of
which 20 were controls, 19 had right cerebral lesions and 20 had left cerebral lesions.
A statistically significant difference in mean scores between the group with right
cerebral lesions and the group with left cerebral lesions was observed. They reported
test-retest reliability as being marginal (r = .69) however Vanier et al. (1990) pointed
out that hemi-neglect is a fluctuating phenomenon and therefore comparison of
performance on the two tests should not be expected. When establishing concurrent
validity, this test was found to identify a much higher percentage of stroke patients
with visual inattention than the Albert‟s Test of Visual Neglect (Vanier et al., 1990)
and the Diller Test (Mercier, Audet, Herbert, Rochette, & Dubois, (2001). In another
study, the authors found that the distractor items on the Bells test tended to detect
mild and moderate neglect more readily (Marsh & Kersel, 1993).
The test consists of a 21.5 x 28 cm sheet of paper on which seven vertical
sections each containing 35 distractor figures (e.g. bird, key, apple, mushroom, car)
and five target figures (bells) are presented. All figures are presented as solid black
silhouettes. The target figures are arranged so that five each appear in seven equal
columns on the page. The number of distractor figures also remains constant.
Administration.
The examinee was first presented with a demonstration sheet that included the
target figure in the centre surrounded by all the distractor figures. The participant
was asked to identify each figure, thus ensuring correct recognition for each object.
The test copy was then presented and the participant was required to identify and
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draw a circle around all the bells on the sheet. Performance on the Bells Cancellation
Test is not timed.
Scoring.
Scoring consisted of the number of bells correctly circled and the time for
completion of the task. The total number of omissions in the three left segments
versus the centre and the three right segments was then compared to normative data
for non-neurologically impaired adults and to norms for those with left or right CVA
(Gauthier et al., 1989).
Other Neuropsychological Baseline Measures.
The following selection of neuropsychological tests were administered at
baseline in order to obtain measures of cognitive domains other than attention. Those
domains included executive functioning, language and verbal and visual memory.
These neuropsychological measures were administered again at six months poststroke for data pertaining to the START project (Barker-Collo et al., 2009)
Executive Functions.
The Stroop Test: Victorian Version (Regard, 1981).
The Victorian Stroop Test is a shorter version of the original Stroop Test
(Stroop, 1935) taking approximately five minutes to administer. It is used to
determine the ease with which a person can maintain a goal in mind and suppress a
habitual response in favour of an unusual one (Spreen & Strauss, 1998). This task
requires the examinee to correctly name the colour of the ink used for written words
which are the names of colours and incongruent to the colour of the print used. This
measure of selective attention and cognitive flexibility is routinely used when
screening for brain dysfunction, and is used in a wide variety of other applications
including testing for Attention Deficit Hyperactivity Disorder (Assef, Gotuzo, &
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Capovilla, 2007; King, Colla, Brass, Heuser, & von Cramon, 2007; Lavoie &
Charlebois, 1994; Wodka et al., 2008), Posttraumatic Stress Disorder (Beers & De
Bellis, 2002; Constans, 2005) and Schizophrenia (Grapperon & Delage, 1999; Henik
& Salo, 2004). The Stroop Test also appears to be sensitive to severity of dementia
(Koss et al., 1984, as cited in Spreen and Strauss, 1998) and has been a primary
measure in studies on the efficacy of APT (Kurtz et al., 2001).
The Stroop Test is negatively impacted by reading ability, and slower with
advancing age has also been consistently documented (Boone, Victor, Wen, Razani,
& Ponton, 2007; Obler, Fein, Nicholas, & Albert, 1991; Spreen & Strauss, 1998, as
cited in Lezak et al., 2004). Performance is also affected by education and culture, to
a lesser degree, but not by gender (Macleod, 1991; Protopapas, Archonti, &
Skaloumbakas, 2007). Test-retest reliability coefficients were high (.90, .83, and .91)
for the three parts of the test, when university students were tested with a one-month
interval between tests (Bullock et al., 1996, as cited in Strauss, Sherman, & Spreen
2006). However practise effects have been found to impact on performance (Spreen
& Strauss, 1998). In a factor analysis the Stroop was found to draw on speed of
processing skills and conceptual abilities, and related to the Block Design, Digit
Symbol and Digit Span subtests (Graf et al., 1995, as cited in Spreen & Strauss,
1998). Other studies have found a moderate relation with the PASAT (MacLeod &
Prior as cited in Spreen & Strauss 1998) and the Tower of London (Hanes et al.,
1996, as cited in Spreen & Strauss, 1998).
Administration.
The task involved the presentation of three white cards 21.5 x 14cm, each
containing six rows of four items printed in green, blue, yellow, or red ink. The four
colours were presented in pseudo-random order on the card although each colour
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appeared once in each row. The stimuli on the first card (Card 1) were dots. When
presented with the first card (Card 1), the participant was required to read as quickly
as possible the colour of each of the 24 dots printed on the card. The stimuli on Card
2 were the words „when‟ „hard‟ and „over‟. When presented with the second card, the
participant was required to state the colour of the print of each of the 24 words
printed on the card. When presented with the final card (Card 3), the task was the
same as that for Card 2, only the stimuli words presented were the colour names
„red‟, „yellow‟, „blue‟, and „green‟. The colours of the print of the words on the Card
3 did not correspond to the content of the words.
Scoring.
Scoring of the three cards included the time it took (in seconds) to complete
each card and the number of errors made on each card. Any spontaneous corrections
made by the examinee were scored as correct. A discrepancy score was obtained
from the difference in time taken to finish the coloured colour names trial (Card 3),
compared with the baseline dots condition (Card 1). These results were compared to
the normative data available for the Victorian version of the Stroop for 17 to 90 +
year olds (Bullock, Brulot, & Strauss, cited in Spreen & Strauss, 1996).
Memory.
California Verbal Learning Test-II (CVLT-II; Delis, Kramer, Kaplan, & Ober,
1987).
The CVLT-ІІ is a multiple-trial list learning task and a widely used
neuropsychological test used for the assessment of the processes and effectiveness of
the strategies (semantic associations) involved in memory and learning verbal
material. The CVLT-ІІ has normative data for individuals aged 16-89 years. Lezak,
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(1995) considers the CVLT-ІІ to be more ecologically valid than other similar
assessments of word list learning.
Reliability studies conducted by the authors of the CVLT-ІІ show high internal
consistency with split-half reliability correlation coefficients from Total Trials 1-5,
ranging from .87 to .89 (Delis, Kaplan, Kramer, & Ober, 2000, cited in Lezak et al.,
2004). Test-retest (21 days later) reliability was also found to be high for Total Trials
with .82 however reliability was much less for other variables such as Total Learning
Slope (.27) and Total Repetitions (.30). A number of factor analyses have consistently
shown a general verbal learning factor with small effects of response discrimination,
learning strategy, proactive interference, and serial position (Lezak et al., 2004). A
four factor model incorporating attention span, learning efficiency, delayed recall, and
inaccurate recall was proposed by Wiegner and Donders, (1999). Performance on the
CVLT-11 is affected by age, gender and education accounting for 29%, 5.1% and
4.5% of the variance respectively (Delis, Kramer, Kaplan, & Ober, 1987).
Administration.
The examinee was presented with 2 verbal lists (List A & B) of 16 words
containing items that were grouped into four different semantic categories (i.e., types
of furniture, vegetables, ways of travelling and animals). Words from the same
semantic grouping are never presented consecutively. The words were presented at a
rate slower than 1 per second. List A was presented over five trials and immediately
after each trial, the participant was required to recall as many of those words as
possible. After the fifth trial a 16-word interference list (List B) containing two extra
categories was presented followed by a short delay free-recall and short delay cuedrecall of List A. After a 20-minute delay, long-delay free and long-delay cued recall
followed by a yes/no recognition trial of List A was administered.
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Scoring.
Raw scores on each trial were converted to standard scores (z-scores) based on
age and gender appropriate norms. The z-scores were rounded to whole numbers.
Data from the following recall measures obtained for this study were obtained: List A
Trial 1; Short-Delay Free Recall; Long-Delay Free Recall; Recognition Hits; and
False Positives.
Wechsler Memory Scale-III (WMS-III; Wechsler, 1997) Logical Memory
subtest (LM).
LM is a measure of verbal learning and memory for conceptual material
presented in the auditory modality and is reflective of memory for everyday
conversation (Spreen & Strauss, 1991). As part of the WMS-III, the LM is used
widely in the detection of memory impairment for patients with TBI. It is
administered as part of the Iowa Screening Battery for Mental Decline and is
therefore a frequently used neuropsychological tool for dementia. Other populations
upon which LM is administered, include patients with Huntington‟s Disease,
Parkinson‟s Disease, Multiple Sclerosis, Epilepsy, and patients with carotid artery
disease and cerebrovascular disease (Diamond et al., 1992; Johnson, Storandt, &
Balota, 2003; Lezak, 1995; McKinlay, Grace, Dalrymple-Alford, & Roger, 2010;
Pelosi, Geesken, Holly, Hayward, & Blumhardt, 1997; Romero et al., 2009;
Schneider, Boyle, Arvanitakis, Bienias, & Bennett, 2007; Waldstein & Katzel, 2005;
Wechsler, 1997).
Split-half reliability estimates for LM immediate recall range from .67 to .80
with an average of .74; and for LM delayed recall range from .55 to .85 with an
average of .75 (Wechsler, 1987). Another study reported a reliability coefficient of
.71 (Mittenberg, Burton, Darrow, & Thompson, 1992). Wechsler found inter-scorer
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reliability for LM was very high at .99, a similar finding to that of McGurie and
Batchelor (1998) whose sample consisted of neurosurgery patients. Practise effects
were demonstrated in average gains of between one and a half and two raw score
points on immediate recall and two and a half to almost three raw score points on
delayed recall (Wechsler, 1987). Factor analysis yielded two factors; a general
memory and learning factor and an attention and concentration factor (Elwood,
1991).
Administration.
LM examines the immediate and delayed recall of two orally presented short
prose passages (Story A and B), each of which contains 25 ideas or units of
information. On this task, Story A and Story B were read aloud to the participant,
after which immediate free recall of that passage was required. A second recall of
Story B was then required. The delayed recall condition involves recall of each
passage (without prior warning) approximately 30 minutes after the administration of
the immediate recall condition. The story was not read out aloud on the delayed
recall condition. On all conditions the participant was asked to recall the story
verbatim.
Scoring.
A point was scored for each correct idea recalled from the passages, with a
maximum score of 50. The total score for both immediate and delayed conditions is
the total number of ideas recalled on both stories for each condition. The total raw
scores for immediate and delayed memory are converted to scaled scores using age
standardised norms.
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Wechsler Memory Scale-Revised (WMS-R; Wechsler, 1987).
Visual Paired Associates (VPA).
VPA is among the most widely used instruments for assessing visual memory.
This test pairs abstract line drawings with colours, and a colour pointing response is
required on immediate and delayed conditions. The test-retest reliability coefficient
ranged from .31 to .68. In factor analytic studies, VPA loaded onto a nonverbal
memory factor or a visual concentration/visual memory factor (Bornstein & Chelune,
1988; Leonberger et al., 1991, as cited in Moye, 1997). As a subtest of the WMS-R,
the VPA has been used extensively with neurologically impaired patients for the
detection of memory deficits and is also utilised in research studies such as assessing
cognitive effects of anti-hypersensitive drugs in the elderly (Louis, Mander, Dawson,
O‟Callaghan, and Conway (1999), and memory impairment in psychosis (Brewer et
al., 2005) and post-cardiac surgery (Jonsson et al., 1999).
Administration.
The subject was shown six nonsense line drawings, each quite different, and
each paired with a square of a different colour. As they looked at the figures they
were instructed to remember the colour that goes with each figure. After they were
shown the figures with their respective colours, they were then shown the figures in a
different order, without their colours, and were asked to indicate the appropriate
colour (from an array of six) that was associated with each figure. If they answered
incorrectly, the correct colour was pointed out to them. The set of six figures were
presented three times followed by a recall trial. If the examinee answered all six items
correctly on or before the third trial, the subtest was discontinued after three sets. If
any of the items on the third set were incorrect, a fourth, fifth and sixth set were
administered if necessary. The examiner continued to correct any incorrect answers.
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The subtest was discontinued when the participant answered all six items of the third
or any subsequent set correctly, or after the sixth set, whichever came first. For each
correct response one point was scored. A delayed recall trial was administered
approximately 30 minutes later, in which the participant was shown the six figures
and asked to indicate which colour went with which figure. The correct figure-colour
pairings were not present prior to the delayed recall trial. For each correct response
one point was scored. Corrective feedback was not given during the delayed recall
trial.
Scoring.
The total score for the immediate recall trial was the sum of correct responses
across the first three sets only. The total score for delayed recall was the total number
of items correctly recalled with a maximum score of six. The raw scores of the
subtest were converted to z scores using the means and standard deviations of raw
scores on subtests by age for the standardisation sample of the WMS-R (Wechsler,
1987).
Rey-Osterrieth Complex Figure (ROCF) (Rey, 1941; Osterrieth, 1944).
The ROCF is a complex diagram that is widely used for the assessment of
visuospatial constructional ability organisation and visual memory. It draws on such
cognitive domains as planning and organisation, problem-solving strategies as well as
perceptual and motor functions. The ROCF is a task that requires the examinee to
copy a complex figure and then replicate that figure at later stages from memory.
A number of studies have found high (r = .91) inter-rater reliability for this test
(Berry, Allen & Schmitt, 1991; Delaney, Prevey, Cramer, & Mattson, 1988).
Repeated administration of the same version of this test resulted in significant
practise effects in normal adults (Spreen & Strauss, 1998). There are a number of
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alternate versions of the ROCF, which help reduce practise effects (Hamby, Wilkins,
& Barry, 1993; Yasugi & Yamashita, 2010). Reliability coefficients between the
ROCF and Taylor Figure suggest the two measures are comparable (Hubley, 2010).
Performance on the ROCF is impacted by age (Spreen & Strauss, 1998) and
education however, there is conflicting evidence regarding the influence of gender
(Freides & Avery 1991; Lezak, 1995). In a sample of patients with neurological
disorders the four trials of ROCF were found to have high concurrent validity with
other commonly used neuropsychological tests including the Benton Visual Retention
Test, the Rey Auditory Verbal Learning Test, Form Discrimination, Hooper, Trails B
and the Token Test (Spreen & Strauss, 1998). The ROCF is also used extensively in
studies of stroke patients (Blake et al., 2002; Phillips & Mate-Kole, 1997; Rapport,
Dutra, Webster, Charter, & Morrill, 1995; Szabo et al., 2009). Indeed, the ROCF has
been included in the National Institute of Neurological Disorders and StrokeCanadian Stroke Network‟s (NINDS-CSN) protocol for cognitive testing (Greenberg,
2009).
The manner in which the two recall trials are drawn can provide valuable
information for the examiner. Patients whose errors are based on poor recall of the
details of the structure tend to have left hemispheric lesions whereas people with right
hemispheric lesions often have difficulty recalling the overall larger structures. The
ROCF is sensitive to the detection of traumatic brain injury with significant deficits
produced by patients with mild head injuries. Behaviours of executive dysfunction
such as perseveration, confabulation, personalisation or other distortion of the design
tend to be exhibited on long-delayed trials.
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Administration.
For this study four conditions of the ROCF were used; the copy trial, the
immediate recall trial, the delayed recall trial and the recognition trial. On the copy
condition, the participant was required to produce a copy of the complex figure on a
separate blank A4 page. After three minutes the immediate recall condition, was
administered. This time the participant was required to produce the figure from
memory, without prior warning. The delayed recall condition was administered
approximately 30 minutes later and again the participant was required to produce the
figure from memory. A recognition trial was administered immediately after the
delayed recall trial. On the recognition trial the participant was shown a booklet
containing 24 details, 12 of which were part of the original figure and 12 that were
not. The participant was asked to circle those details that belonged in the original
figure.
Scoring.
The figure is divided into 18 scorable details with points awarded to each detail
depending on accuracy, distortion and location of its reproduction. Two points are
awarded for each detail that is accurate and properly placed. One point is awarded for
an accurate copy that is poorly placed. One point is awarded if a detail is distorted or
incomplete but recognizable and placed properly and a half point is awarded if a
detail is distorted or incomplete but recognisable and placed poorly. No points are
awarded if the detail is absent or not recognisable. The maximum points scored, is 36
for each trial i.e., the copy, immediate and delayed trial. Two points are awarded for
each correctly identified figure on the Recognition trial giving a maximum of 24
points.
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Language.
Boston Naming Test (BNT) – 60 item version (Kaplan, Goodglass, &
Weintraub, 1983).
The BNT is a widely used confrontation naming test in English-speaking
countries (Barker-Collo, 2007). Utilised for the purpose of assessing the ability to
name pictured objects, it is sensitive to subtle word-finding difficulties as well as to
subcortical brain disease or damage (Lezak et al., cited in Sbordone, Saul & Arnold,
2007).
Sawrie, Chelune, Naugle, and Luders (1996) reported that test-retest reliability
after 8 months was high (.94) in 51 participants with intractable epilepsy. Concurrent
validity with other tests of language tests has also been found to be high (Spreen &
Strauss, 1998). Split-half correlations for the original version were in the .71 to .82
range for a small control group of normal elderly people and at .97 for a group of
Alzheimer patients with the latter group producing scores significantly below the
control group (Huff, Collins, Corkin, & Rosen, cited in Lezak, 1995). The original
version of the BNT contains 85 items however, a revised 60-item version with well
standardised data across ages, from 5 years through to 97 years. This revised version
is used in virtually all cases (Kaplan, Goodglass, & Weintraub, 1983) and was used in
this study.
Administration.
The participant was presented with 60 cards, each with an ink line drawing of
objects representing a range of simple high-frequency words (tree) to rare words
(abacus). Each card was presented one at a time and the participant was asked to
name the object. If the participant did not provide an answer, or provided an
incorrect answer, within 20 seconds, a stimulus or phonemic cue was provided. The
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standard discontinuation criterion of failure to correctly name objects on six
consecutive trials was used. Administration of this test was approximately 10 – 20
minutes.
Scoring.
Each correct answer received a score of 1 if the answer was spontaneous or
followed a stimulus cue. A correct answer following a phonemic cue received a score
of 0. Administration of the test began with item 30 (harmonica) and full credit (30
points) was given for items 1 to 30 if the participants gave the correct answer. If
either item 30 or 31 did not receive a correct answer (one point), then items were
administered in reverse order until a total of eight consecutive preceding items were
passed. Administration in a forward direction was then resumed. The total maximum
score may range up to 60 and raw scores were converted to standard scores using age
related norms.
Controlled Oral Word Association (COWA) (Benton & Hamsher, 1989).
The COWA is widely used in clinical neuropsychology as a measure of verbal
fluency (Iverson, Franzen & Lovell, 1999). The object of the COWA is to say as
many words as possible that begin with specified letters. There are two commonly
used versions of this test; one uses the letters F, A, S and the other uses C, F, L
although evidence suggests the CFL version is harder than the FAS version (Barry,
Bates & Labouvie, 2008). In this study, the FAS version was used.
The purpose of this easily administered test is to assess verbal fluency and the
spontaneous production of words beginning with a specific letter, within a given time
frame. It is thought to determine whether an individual can access a strategy to guide
their search for words rather than lexicon definition, and is associated with frontal
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lobe function (Penndleton, Heaton, Lehman, & Hulihan, 1982; Phelps, Hyder,
Blamire, & Shulman, 1997). It is widely used in the detection of brain injury.
The COWA is included in the Neurosensory Center Comprehensive
Examination for Aphasia (NCCEA) (Spreen & Benson as cited in Spreen & Strauss,
1998). It is also frequently used as one of the measures of dementia, although the
underlying defects across disorders, differs. For example in patients with Parkinson‟s
Disease, the reduced capacity to generate words, lies in the mental inflexibility of
these patients, however in patients with Alzheimer‟s Disease the underlying problem
lies reduced semantic processing and recall (Lezak, 1995). The COWA is also used
in research with many other populations including patients with HIV (Dolan et al.,
2003), Korsakoff‟s disease, (Dirksen, Howard, Cronin-Golomb, & Oscar-Berman,
2006), Huntington‟s disease (Backman, Robins-Wahlin, Lundin, Ginovart, & Farde,
1997), and stroke (Blake et al., 2002; Suhr, Grace, Allen, Nadler, & McKenna, 1998).
Re-test reliability for this test has ranged from .88 after 19-42 days (des Rosiers
and Kavanagh, as cited in Spreen & Strauss, 1988), to .65 after eight months for
patients with intractable epilepsy, 70 after one year (Sawrie et al. cited in Sbordone et
al., 2007) and .74 after an interval of five years (Tombaugh, Kovak, & Rees, 1999).
This test has also been found to have high concurrent validity with other language
tests and appears to be sensitive to word-finding difficulties as well as subcortical
disease and brain damage (Lezak et al., cited in Sbordone et al., 2007). In their
presentation of normative data for the FAS measure of verbal fluency, Tombaugh,
Kozak, and Rees (1999) found that education accounted for more of the variance in
performance than age (education = 21.7% vs age = 11.8%). However, it is the ability
to initiate and maintain effort and organise information for retrieval, abilities which
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are sensitive to the aging process that is required to perform well on this task, (Barry
et al., 2008).
Administration.
On this version of the COWA, trials using the letters F, A & S were used. The
frequency of use of these letters in the English language ranges from high for the first
letter (F) to a lower frequency for the second letter (A) and a further lower frequency
for the third letter (S). On the first trial the participant was asked to say as many
words as they could think of that began with the letter F. They were instructed to
exclude proper nouns, numbers and the same word with a different suffix. The same
procedure was conducted for the second trial except the specified letter was A. The
third trial was then administered and this time the specified letter was S. The
participant was given 1 minute for each trial.
Scoring.
All answers were written down verbatim. The score was the sum of all
admissible words across the three letter trials. All non-words, repetitions and proper
nouns were excluded. Norms for both males and females according to age and
educational level are available. Raw scores were converted to standardised scores
and compared to available normative data (Strauss, Sherman, & Spreen, 2006).
Health-Related Quality of Life (HRQoL).
One of the often cited problems with cognitive research is that it is difficult to
translate the findings into real-life situations. It was therefore decided to utilise
health related quality of life measures in an attempt to determine if improving
attention deficit has wider benefits to the individual other than possible cognitive
improvement. Thus, the Mental Component Summary (MCS) score of the Medical
Outcomes Study 36-item Short Form questionnaire (SF-36) was used as the
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secondary outcome measure and was administered at baseline and at postintervention. All other health related quality of life measures (CFQ, mRS, & GHQ)
were administered at baseline and at six months post-stroke.
SF-36.
The SF-36 is a widely used generic instrument for measuring quality of life
designed for use in clinical practice and research for many diseases and conditions
including stroke patients (de Haan, 2002; Dorman, Slattery, Farrell, Dennis, &
Sandercock, 1998; Hackett et al., 2000; Williams, Weinberger, Harris, & Biller,
1999). The SF-36 has been tested for validity and reliability across various
populations (Fukuhara, Bito, Green, Hsiao, & Kurokawa 1998; Sanson-Fisher &
Perkins, 1998) including Maori, Pacific and New Zealand European ethnic groups
(Scott, Sarfati, Tobias & Haslett, 2000; Scott, Tobias, Sarfati,& Haslett, 1999).
It comprises 36 self-rated items organised into eight scales; 1) Physical
Functioning, 2) Role limitations because of physical health problems, 3) Bodily pain,
4) Social functioning,5) General mental health (psychological distress and
psychological well-being), 6) Role limitations because of emotional problems, 7)
Vitality (energy/fatigue), and 8) General health perceptions, with each scale scored
out of 100 points. Each scale has been standardised to have a mean of 50 and
standard deviation of 10. Higher scores are associated with better HRQoL (Ware et
al., 1994). The Mental Component Score (MCS) is comprised of four of those scales;
Vitality, Social Functioning, Role Emotional and Mental Health, with each scale
scored out of 100 points. The MCS score was used for this study.
modified Rankin Scale (mRS) (Rankin, 1957).
The Modified Rankin Scale is a commonly used scale for measuring the degree
of disability or dependency in the daily activities of people who have suffered a
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stroke. It is also a widely used measure in stroke clinical trials (Banks & Marotta,
2007; Sulter et al., 1999). The level of disability or independence is defined on 6
levels (grade 0 to level 5) with Level 0 reflecting no disability and each subsequent
level from 1 to 5 indicative of more severe disability with 6, denoting death. The
MRS has high correlation with other post-stroke disability indexes including the
Barthel Index (BI) and the motor component of the Functional Independence Measure
(M-FIM) (Kwon, Hartzema, Duncan, & Min-Lai, 2004). However, unlike the BI and
the M-FIM, the MRS is heavily weighted toward global disability and as such allows
for consideration of non-physical attributes, such as cognition and language that may
contribute to disability (Banks & Marotta, 2007). Inter-rater reliability has been
found to be moderate to nearly perfect and can be improved with the addition of
structured interviews (Banks & Marotta, 2007). Patients with a score ≤ 2 on this
scale, by definition are independent (Uyttenboogaart, Luijckx, Vroomen, Stewart, &
De Keyser, 2007).
Cognitive Failures Questionnaire (CFQ). (Broadbent, Cooper, FitzGerald &
Parkes, 1982).
The CFQ was developed to explicitly investigate a person‟s propensity for
committing a cognitive failure and are the reported difficulties people experience in
typical everyday situations (e.g., forgetting names or misinterpreting directions) that
are linked to lapses in controlled processes, such as focus of attention and working
memory (Austin, Mitchell, & Goodwin, 2001; Wallace, 2004). The CFQ is a 25 item
self-report assessment that measures the frequency of everyday cognitive failures or
lapses (e.g. Q.2 Do you find you forget why you went from one part of the house to
the other? Q. 20. Do you find you forget people‟s names? ) that have occurred in the
previous six months. Participants were asked to respond to items using a 5 point
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Likert scale where 4= very often, 3 = quite often, 2 = occasionally, 1 = very rarely
and 0 = never. Scores therefore range from 0 to 100.
General Health Questionnaire (GHQ-28). (Goldberg & Williams, 1988).
The GHQ-28 is a shortened version of the original 60-item General Health
Questionnaire and is used for the detection of psychiatric distress related to general
medical illness (Lykouras et al., 1996). The GHQ has four subscales (each with 7
items) representing dimensions of symptomology; somatic symptoms, anxiety and
insomnia, social dysfunction and severe depression. It is not a diagnostic tool but
rather one that may indicate the need for a formal psychiatric interview. The
participant‟s responses to the self-report questionnaire are based on their health state
over the previous two weeks. The questionnaire takes approximately 15 minutes to
administer and score. Scores range from 0 to 28 with higher scores indicating a
greater probability of psychiatric distress (Goldberg & Williams, 1988). The strength
of the General Health Questionnaire lies in its acceptability across a wide range of
clinical settings and cultures, and its appropriateness with all age ranges from
adolescents through to adults (Goldberg et al., 1997; Rush, First, Blacker, & APA.,
2008).
Primary Outcome Measure.
The Full Scale Attention Quotient of the IVA-CPT was the primary outcome
measure used to gauge improvements in attention. A clinically significant change on
this test was defined as one standard deviation.
Secondary Outcome Measure.
The Mental Component Summary (MCS) score of the Medical Outcomes Study
36-item short Form questionnaire (SF-36) was used as the secondary outcome
measure.
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Intervention - Attention Process Training-I (APT-1), (Sohlberg & Mateer, 1987).
APT-I is a theoretically based, hierarchical, multilevel cognitive therapy
programme that is used by neuropsychologists, occupational therapists, speech
language therapists and other qualified rehabilitation therapists for the purpose of
remediating attention deficit. This programme has been designed to provide activities
that target the four components of attention i.e., sustained, selective, alternating and
divided attention. The APT-1 programme consists of a series of auditory and visual
tasks that become progressively more difficult. The APT manual provides a
hierarchy for the administration of each task however the specific order of each
exercise was defined prior to commencement of treatment, by the researcher who
conducted a trial run of the APT on academic staff. The authors (Sohlberg and
Mateer) of APT were advised via email of the order and responded by endorsing the
proposed order. (See Table 6 showing the order in which APT tasks were
administered).
Administration of APT.
Each auditory exercise was presented at a slow (A) or fast (B) pace thus
allowing for targeting of speed of information processing. Directions were delivered
at the beginning of each exercise by a male voice heard on a compact disc (CD) and
speakers connected to a laptop computer. The treating neuropsychologist confirmed
with the participant that they understood the directions.
All participants began the programme with exercise no. 1 and proceeded
through the programme as each exercise was “mastered‟, which was defined as an
85% or greater success rate and no less than a 35% decrease in time (for timed
activities) from baseline trials. As well as target responses, non-target responses were
also recorded thereby providing information for impulsivity. Table 6 outlines the
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sequence in which the exercises were administered, the number of exercises for each
type of task, the mode of delivery and which component of attention was being
targeted. Altogether the programme consisted of 116 separate exercises.
Every participant received feedback after each activity and open discussion on
the participant‟s experience was encouraged. If a participant was frustrated and
became discouraged by non-mastery of an activity, they were presented with another
task and returned to the previous task at a later stage. On some occasions, the
participant was unable to master the fast trial of a particular activity but was able to
master the slow trial of the activity next up in the hierarchy.
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Table 6
The order in which APT tasks were administered (the number in brackets depicts the order in which the tasks
were administered)
Type of
Attention
Activity
Auditory
Visual
Sustained
1
2
3
4
(1) Attention CD 1 (exercises 1-24)
(4) Attention CD 2 (exercises 34-42)
(5) Serial Numbers (exercises 43-48)
(6) Attention CD 4 (quiet) (exercises 49-58)
1
2
(2) Shape Cancellation (exercises 25-30)
(3) Number Cancellation (exercises 31-33)
Selective
5
6
7
(7) Attention CD 2 (noise) (exercises 59-66)
(8) Attention CD 3 (noise) (exercises 67-86)
(9) Attention CD 4 (noise) (exercises 87-92)
3
4
(10) Shape Cancellation with Overlay (exercises 93-98)
(11) Number Cancellation with Overlay (exercises 99-101)
5
6
7
8
9
(12) Flexible Shape Cancellation (exercises 102-107)
(13) Flexible Number Cancellation (exercises 108-110)
(14) Odd & Even number identification (exercise 111)
(15) Addition/Subtraction Flexibility exercise 112)
(16) Set Dependent Activities I and II (exercises 113-114)
10
(18) Card Sorting (exercise 116)
Alternating
Divided
8
(17) Dual Task: Combine Attention CD and
Cancellation Tasks (exercise 115)
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Sustained Attention Tasks.
Auditory Tasks
There were two types of auditory tasks involving different formats. On the
first set of tasks, participants were required to listen to a male voice on CDs 1, 2
& 4and press the buzzer each time a target stimulus was identified. For example,
an early task (Exercise 2) required the participant to identify (by pressing a
buzzer) a single number (e.g. 1) amongst a list of random numbers being read out.
In total there were 41 exercises designed to target sustained attention, with the
target stimuli becoming more complex on each consecutive exercise. For
example, on Exercise 14 the participant was required to press the buzzer to
identify 2 consecutive numbers (e.g. 6, 7) and on Exercise 34, the participant was
required to press the buzzer to identify 2 months that had been read out in the
correct descending order (e.g. May, April). More complex exercises such as
solving math problems required the participant to give a verbal response (Ex 49Ex 58).
The second group of auditory tasks (Serial Numbers) is a task of mental
subtraction and requires the participant to count backwards by a given number
(e.g. 1) beginning at a defined number (usually 100). On subsequent trials, the
number to count backwards, were 3, 4, 6 and 7. On the final trial the participant
beginning with the number 100, was required to count backwards by mentally
subtracting 6, then adding 1. The time it took to complete the task plus the
number of errors made were recorded on the appropriate score sheet. If the
participant completed the task fluently and accurately at baseline they would
automatically proceed to the next exercise.
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Visual Tasks
The visual tasks were presented as shape or number cancellation tasks.
On shape cancellation tasks the stimulus sheets contained rows of random shapes
and shape features and the participant was instructed to cross out with a pencil,
target shapes or shape features. Each stimulus sheet contained many different
shapes with subsequent sheets containing more complex shapes. Complexity was
further increased by instructing the participant to simultaneously cross out two
target shapes on the stimulus sheet, thereby providing 12 exercises for this type of
task. Performance, including time and number of errors, was noted on the
scoresheet provided in the APT package.
On number cancellation tasks the participants were given a sheet containing
random numbers and instructed to cross out target numbers. The participant was
instructed to work from left to right, line by line, down the page as quickly and
accurately as possible. There are nine trials of this type of exercise, with a
different target number for each trial. After each block of three different target
numbers, consecutive stimulus sheets contained more numbers due to the
increasingly smaller print, therefore each block was deemed to be more difficult
than the previous block. Timing commenced when the command “go” was given
and the number of errors and time was recorded in the appropriate scoresheet.
Selective Attention Tasks.
Auditory Tasks.
These tasks were identical to the auditory tasks for sustained attention with
the addition of background noise. The participant was required to listen to CDs 2,
3, and 4 select and respond to the target stimulus while simultaneously inhibiting
a response to the extra stimulus. On all auditory tasks, the CDs were arranged in
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hierarchical fashion from easier to more difficult and were presented at a slow or
fast pace. Complexity of the task was increased by instructing the participant to
press the buzzer after identifying 2 target stimuli. Scoring on these tasks included
the number of errors made and the number of false alarms.
Visual Tasks.
These tasks were identical to the shape and number cancellation tasks with
the addition of a distractor overlay that introduced “visual noise”. The participant
was required to cross out the target stimulus while simultaneously inhibiting a
response to the additional design. Complexity of all visual cancellation tasks was
increased by instructing the participant to cross out either two numbers or target
shapes or shape features.
Alternating Attention Task
Flexible Number & Shape Cancellation.
This component of attention was presented in the visual mode only and was
similar to the shape and number cancellation tasks. Participants were required to
alternate between identifying two different numbers or target shapes or shape
features, on the stimulus sheet in response to the command “change”. For
example, the participant began by crossing out all of the numbers “3” and upon
the command “change” would then draw a slash mark and begin crossing out all
of the numbers “6”. When the stimulus sheet contained shapes, the target shapes
or shape features were identified prior to commencing the task and again the
participant would alternate between those stimuli on the command “change”.
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Odd & Even number identification.
The participant was presented with a sheet containing random numbers and
the participant was required to alternate between circling an odd or even number
every 15 seconds, on the command “change”.
Addition/Subtraction Flexibility.
The participant was presented with a sheet consisting of pairs of numbers.
On the command “change” which occurred every 15 seconds, the participant was
required to alternate between adding and subtracting the pairs of numbers.
Set Dependent Activities I.
The participant was presented with a sheet containing the words “big” and
“little” printed in incongruous sizes. The participant was required to read the
actual words as they appear and on the command “change” after every 15
seconds, the participant was required to switch to naming the size of the type.
Set Dependent Activities II.
The participant was presented with a sheet containing the words “high”,
“mid” and “low” printed in incongruous line positions. The participant was
required to read the words as they actually appear and on the command “change”
after every 15 seconds, switched to reading the line position of the words,
ignoring the words themselves.
Divided Attention Tasks
Auditory Tasks.
This activity required the participant to respond to the auditory stimuli on
the attention CD while performing a concurrent visuo-motor task with the shape
or number cancellation tasks.
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Visual Tasks.
The participant was required to sort a deck of cards by suit while
simultaneously turning face down any cards that contain a certain target letter in
the spelling of their name (e.g. „e‟ appears in the names ten, queen etc.).
Design Overview
The apparatus and measures described above were administered at four stages
throughout this study. First, the MMSE was administered to establish inclusion
then the attention measures were administered to establish an attention deficit.
This was followed by administration of the Barthel Index and all other
neuropsychological measures. Finally all health related quality of life measures
were administered. At the follow-up stage, all the attention measures and the SF36 were re-administered. (See Table 5 for schedule of assessments).
Procedure
Inpatients of neurological wards of two major New Zealand hospitals
Middlemore Hospital and North Shore Hospital were approached to take part in
the study. Participants were identified at the daily triage of the rehabilitation
wards, at the twice weekly multi-disciplinary team meetings held in the acute
stroke ward of Middlemore Hospital or by referral from key hospital staff at both
hospitals. Recruitment of participants took place over an 18 month time period.
Only those stroke survivors who met the eligibility criteria were invited to
participate in the study. All participants were provided with a patient information
sheet (See Appendix C) describing the study and a Consent Form (See Appendix
D), and given the opportunity to discuss the procedures with research staff before
consenting to take part. The consent forms were signed and dated by the
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participant. All participant data was secured in a locked filing cabinet onsite and
transferred to the University of Auckland every week where it was again stored in
a locked cabinet in a secured room where it will remain stored for 16 years.
After obtaining medical officer consent, patients with first-ever stroke were
approached within 4 weeks after stroke (M = 18.6 days post-stroke; SD = 7.6), and
provided with a written and verbal description of the study in which they were
then invited to take part. Patients who had already been discharged from hospital
were contacted by phone and provided with a description of the study. Data
including age, education, marital status, gender, days since stroke, side of lesion,
and stroke subtype according to the Oxford classification was obtained from the
patient‟s medical records or from the participants themselves. They were also
administered the MMSE and were required to score ≥20 to be eligible for
inclusion into the study. All participants were then scheduled to meet with the
research associate (usually within 24 hours) for the purpose of administering the
IVA-CPT, PASAT, TMT, and Bells Cancellation Test to determine the presence of
an attention deficit. Those participants who did not have an attention deficit as
per our criteria were advised and thanked for their participation. The 84 patients
identified as having an attention deficit were administered the Barthel Index and
underwent further neuropsychological testing (details of the measures given
above) to obtain baseline data for memory, spatial functions and language, health
related quality of life measures plus other demographic data including other
therapies and health services being received. (See Table 4 for Schedule of
Assessments).
The participants were then randomised into either the standard care group or
the treatment and standard care group. Randomisation was concealed using an
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internet on-line service based at the Clinical Trials Research Unit of the
University of Auckland. Randomisation by minimisation was used to ensure the
balance for possible prognostic factors, namely gender, age (<70yrs, >70yrs),
ethnicity, Barthel Index Score ((18 and above (high) or below 18 (very high), and
hospital site. The participant was then informed whether they had been
randomised into the standard care group or the treatment plus standard care group.
The participants in the standard care group received ad hoc individual therapy
provided to address specific neuropsychological deficits, most notably visual
neglect/inattention which typically involved Occupational Therapy. Speech
Language Therapy, Physiotherapy and other rehabilitation programmes (such as
Stroke Recovery Education) were also part of standard care as required. Those
participants randomised to the APT group received APT in addition to standard
care.
In order to reduce measurement bias, assessments were carried out by a
research associate, blind to the treatment status of the participant, while treatment
was conducted by a neuropsychologist (the author). Participants were also
cautioned not to reveal to the research associate, their treatment status.
Participants who were randomised into the treatment group were scheduled to
start treatment as soon as practicable, which was usually the next day. Follow-up
data was obtained by the research associate during the 5th week after
randomisation and assessment sessions took place either in hospital, at a
rehabilitation in-patient facility, or at the participant‟s home if they had been
discharged from hospital.
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Therapy Regime.
The participants who were randomised into the APT treatment group
received up to 30 hours of individual APT. Thirty hours of treatment was chosen
as this falls within the range of APT treatment lengths reported in evaluations
within the existing literature and is within the usual length of stay in inpatient
neurological rehabilitation units. Participants were scheduled each weekday for
1.5 hours treatment sessions, for four weeks. This treatment schedule was
consistent with other rehabilitation services provided in in-patient neurological
rehabilitation settings. When possible each session was conducted in two forty
minute blocks with a 10 minute break between blocks. Participants began
treatment on the next available day which was normally the day after
randomisation. Treatment took place either at bedside if the participant was in a
single room, in a pre-booked room within the ward, or at the participant‟s place of
residence if they had been discharged. The amount of APT each patient received
varied greatly and was largely determined by the participant‟s tolerance of the
therapy on any particular day.
Compliance was monitored and recorded by the treating neuropsychologist
and included data on the number of hours of total APT training (See Figure 6) and
the tasks that were completed (See Figure 7). Information for when treatment
commenced and ended as well as the reasons for the participant completing less
than 30 hours, was recorded. As can be seen in Figure 7 many more people
progressed through the auditory tasks compared to the visual tasks. The highest
auditory task that was reached was Task 7 however nobody reached the task (Task
8) at the highest level in this modality. Although two participants did reach the
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highest visual task (Task 10), they were also the only two who progressed beyond
Task 3 which was the second level of difficulty in the visual modality.
The clinical data relating to the performance of participants on APT will be
presented in the following chapter as well as the data from statistical analyses. A
discussion on both sets of data will then be presented in the final chapter.
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Chapter 5: Results
In the current study the analyses were conducted in four parts. The focus of
Part 1 of this chapter is the analyses of baseline data. Descriptive data regarding
the demographic characteristics of the participants are presented and statistical
analyses are conducted to compare differences in characteristics between the
Attention Process Training (APT) and standard care groups. Following this, data
regarding the participants‟ performance on the baseline neuropsychological
measures are presented and the findings from statistical analyses comparing
baseline performances between the APT and standard care groups are
summarised. The last part of this section will present data from a series of
correlation analyses conducted to investigate the relationships between baseline
attention measures with demographic variables, functional variables and other
neuropsychological measures.
In Part two of this chapter, the main hypothesis of this study, (i.e.,
examination of the effect of APT on attention deficit in acute stroke patients), was
investigated. A series of 2 x 2, analyses of variance (ANOVAs) were conducted
with APT and standard care as the between-group factor and time at baseline and
post-treatment as the within subjects factor with each of the attention measures as
the dependent variable. The statistical analysis regarding the effect of APT on the
secondary outcome measure, the SF-36, is also reported.
Part three focuses on the qualitative data obtained from the study. All
baseline neuropsychological measures for both APT and standard care groups
were placed into qualitative descriptive categories (e.g., average range, below
average range, etc.) and an examination of the participant‟s changes across
qualitative descriptive categories from baseline to post-treatment was conducted.
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Finally, Part four provides data for those factors that may have influenced
how the participants engaged in the intervention process. Factors investigated
included the relationships between demographics and performance on
neuropsychological measures with how far they reached on both auditory and
visual tasks as well as the number of completed hours of APT.
Part 1: Analyses of Baseline Measures
In order to determine if there were any significant differences between the
demographic characteristics of the APT and standard care groups at baseline, a
series of independent t-tests for continuous variables, a chi square analysis for
gender and Fisher‟s exact test for categorical variables with fewer than 5
frequencies were conducted, the results of which can be seen in Table 7. The
results of the analyses show that the average age for the two groups and their
levels of education were similar. There were a greater number of Maori
participants in the standard care group compared to the APT group but this was
not a significant difference and overall ethnicity was distributed evenly across
both groups. There was also a larger group of widowed participants in the
standard care group compared to the APT group; however, overall marital status
did not differ significantly between the two groups. The majority of participants
in both groups experienced ischaemic strokes and although there were a higher
number of lacunar strokes in the standard care group compared to the APT group,
distribution of the type of stroke was evenly distributed across the two groups.
Left hemispheric strokes were also more predominant in the standard care group
but overall there was no statistical difference between the groups for side of
lesion. The length of time since their stroke had occurred was approximately the
same for both groups. MMSE and Barthel Index scores were similar across groups
121
revealing two groups of similar broad cognitive and functional levels. The latter
was somewhat expected given that the Barthel Index was one of the factors of
randomisation. Although there were more males than females in both groups,
„gender‟ was balanced across both groups. Overall the results of these analyses
show that the two groups were well-balanced for all demographic variables.
Table 7
Demographics of participants randomised to APT group and standard care group
Demographic
APT Treatment
Group n =35
Standard Care
Group n =43
Significance of difference
(X2 FET, or t, p)
69.54 (16.08)
68.51 (15.31)
t(76) = 0.29, p = .77
21 (60)
14 (40)
26 (60.5)
17 (39.5)
X² (1) = 0.002 p >.05
28 (80)
2 (5.70)
4 (11.40)
1 (2.90)
33 (76.7)
7 (16.3)
3 (7)
FET = 3.42, p >.05
2 (5.70)
22 (62.90)
5 (14.30)
6 (17.10)
5 (11.6)
28 (65.1)
2 (4.7)
8 (18.6)
FET = 2.67, p >.05
24 (68.60)
4 (11.40)
2 (5.70)
5 (14.30)
24 (55.8)
12 (27.9)
1 (2.3)
6 (14)
FET = 3.71, p >.05
28 (80)
3 (8.6)
12 (34.3)
1 (2.9)
2 (5.7)
10
2 (5.70)
3 (8.60)
2 (5.70)
40 (93)
3 (7.0)
15 (34.9)
7 (16.3)
3 (7.0)
12
1 (2.3)
0
2 (4.7)
FET = 6.97. p >.05
14 (43.8)
15 (46.9)
3 (9.4)
25(58.1)
18(41.9)
FET = 4.38. p >.05
-18.48 (11.95)
-18.58 (7.61)
t(76) = 0.04, p = .97
14.60 (5.38)
14.33 (5.81)
t(76) = 0.21, p = .83
Age
Mean (SD)
Gender, N (%)
Male
Female
Ethnicity, N (%)
European
Maori
Pacific Island
Indian
Education N (%)
Primary
Secondary
Polytechnic
University
Marital Status N (%)
Married/De Facto
Widowed
Never Married
Separated/Divorced
Stroke Type N (%)
Ischaemic
TACS
PACS
LACS
POCS
Uncertain
Intracerebral
Subarachnoid
Unknown
Hemisphere of lesion N (%)
Left
Right
Unknown
Time since stroke - Days
Mean (SD)
Barthel Index
Mean (SD)
APT = Attention process Training, LAC = Lacunar Stroke, MMSE = Mini Mental State
Examination, N = Number, PACS = Partial Anterior Circulation Stroke, POCS =
Posterior Circulation Stroke, SD = Standard Deviation, TACS= Total Anterior
Circulation Stroke.
122
All raw scores from the neuropsychological tests were standardised
by converting them to z-scores using normative data obtained in respective
test manuals or from a compendium of neuropsychological tests (as noted
on page 80 of the Methods Chapter). Independent-sample t-tests were
conducted to determine if there were significant differences between the
APT group and the standard care group‟s performance/scores on any of the
neuropsychological baseline measures and health related quality of life
measures. For clarity, t-test results are summarised in two separate tables.
Table 8 provides the results for all the attention measures and the SF-36
which were the measures that were administered at baseline and again at
post-intervention. Table 9 provides the results of t-tests for those other
measures that were administered at baseline and at 6 months post-stroke
and include all other neuropsychological measures, plus all other health
related quality of life measures including the mRS, the CFQ and the GHQ.
However, as can be seen in Tables 8 and 9 completion rates varied
considerably across measures. The factor that most influenced noncompletion of the tasks was heightened fatigue where participants were
just too tired to do the task. Other participants were unable to complete
certain measures because of their aphasia, hemiplegia or problems with
vision. A number of participants were overwhelmed by some tasks
(particularly the PASAT) and declined to engage in the task at all.
As can be seen in Table 8 there was a significant difference between
the two groups on the Full Attention Score of the IVA-CPT with the
standard care group obtaining a significantly higher score. Ideally, an
123
analysis of co-variance (ANCOVA) controlling for this difference would
have been conducted, however, this was not possible because the covariate
(the Full Scale Attention score) is not independent from the experimental
effect (the dependent variable) (Field, 2009).
Table 8
Performance of the APT and SC Groups on baseline measures of attention and the SF-36.
(Data represented as z-scores apart from the Bells Test which is the raw score)
APT
SC
Measure
n
M(SD)
n
M(SD)
t-test
IVA-CPT
FSAQ
34
-5.14 (3.40)
40
-3.41 (2.98)
t(72) = -2.33, p = .023*
AAQ
34
-4.16 (3.16)
40
-3.25 (2.79)
t(72) = -1.32, p = .192
VAQ
34
-4.63 (3.79)
40
-3-33 (3.40)
t(72) = -1.56, p = .124
FSRQ
34
-2.79 (3.96)
40
-1.28 (2.79)
t(72) = -1.93, p = .058
APQ
34
-1.54 (3.80)
40
-1.03 (2.95)
t(72) = -0.66, p = .515
VPQ
34
-2.05 (4.05)
40
0.95 (2.80)
t(72) = -1.37, p= .175
TMT
A
28
-2.82 (3.97)
38
-3.70 (5.40)
t(64) = 0.72, p = .472
B
22
-2.24 (2.90)
33
-3.07 (3.70)
t(53) = 0.89, p = .379
PASAT
2.4
19
-1.65 (0.95)
20
-1.57 (0.53)
t(37) = -0.35, p = .731
2.0
19
-1.27 (0.83)
20
-1.26 (1.00)
t(37) = -0.04, p = .971
Bells-Raw scores
Left
32
11.69 (4.92)
43
12.51 (4.66)
t(73) = -0.74, p = .461
Centre
32
4.28 (1.14)
43
4.33 (1.44)
t(73) = -0.14, p = .886
Right
32
13.41 (4.28)
43
13.37 (2.74)
t(73) = -0.05, p = 959
SF-36
35
PCS
35
31.35 (9.91)
43
34.27 (10.66)
t(76) = 1.24, p = .218
MCS
35
46.17 (11.34)
43
42.79 (11.35)
t(76) = 1.31, p = .195
* p = <.05
APT = Attention Process Training, AAQ = Auditory Attention Quotient, APQ = Auditory
Prudence Quotient, FSAQ = Full Attention Quotient, FSRQ = Full Scale Response
Quotient, IVA-CPT = Integrated Visual and Auditory Continuous Performance Test, N =
Number, PASAT = Paced Auditory Serial Addition Test, SC = Standard Care, SD =
Standard Deviation, TMT = Trail Making Test, VAQ = Visual Attention Quotient, VPQ
= Visual Prudence Quotient.
In Table 9 it can be seen that the only significant difference
between the groups was on the CVLT Recognition trial with the standard
care group obtaining significantly lower scores than the APT group at
baseline. To summarise, it was found that the performance of the two
groups differed significantly on two neuropsychological measures, i.e. the
FSAQ of the IVA-CPT and the Recognition trial of the CVLT. The
difference on the FSAQ has implications for the study given that it is the
124
primary outcome measure. However, the results of this analysis show that
overall the two groups were similar on all other measures of attention
other baseline neuropsychological measures and health related quality of
life measures.
Table 9.
Performance of the APT and standard care groups on baseline neuropsychological
measures of executive functions, memory and language and remaining health related
quality of life measures (neuropsychological data are presented as z-scores)
Measure
n
APT
M(SD)
n
sc
M(SD)
t-test
Stroop
Dot
27
-2.01 (2.80)
34
-2.80 (5.54)
t(59) = 0.67, p = .51
Word
27
-2.04 (2.84)
34
-2.49 (3.19)
t(59) = 0.58, p = .57
Colour
27
-0.82 (1.89)
34
-1.18 (3.52)
t(59) = 0.48, p = .63
ROCF
Copy
24
-2.75 (3.91)
33
-3.16 (4.31)
t(55) = 0.37, p = .71
ShD
24
-0.72 (1.67)
32
-0.45 (1.65)
t(54) = -0.61, p = .55
LD
24
-0.91 (1.87)
31
-0.49 (1.77)
t(53) = -0.85, p = .40
Recognition
24
-2.05 (2.80)
31
-1.73 (2.76)
t(53) = -0.43, p = .67
VPA
Learning
30
-0.18 (0.91)
37
-0.55 (1.14)
t(65) = 1.40, p = .16
Delayed
30
-0.25 (0.86)
35
-0.21 (1.09)
t(63) = -0.18, p = .86
LM1
32
0.10 (1.07)
34
-0.09 (1.16)
t(64) = 0.70, p = .49
LM11
32
0.19 (1.07)
34
0.22 (1.12)
t(64) = -0.10, p= .92
CVLT
Trial 1
33
-0.85 (1.28)
40
-0.55 (1.60)
t(71) = -0.87, p = .39
ShD Free
33
-0.65 (1.24)
38
-0.76 (1.33)
t(69) = -0.36, p = .72
LD Free
33
-0.68 (1.19)
40
-1.03 (1.45)
t(71) = 1.09, p = .28
Recognition
33
-1.48 (1.62)
40
-0.65 (1.30)
t(71) = -2.44, p = .02*
BNT
32
-1.11 (2.12)
36
-0.91 (2.36)
t(66) = -0.37, p = .72
COWA
Word
31
-0.95 (1.01)
38
-0.91 (1.11)
t(67) = -0.14, p = .89
mRScale
35
2.66 (1.26)
43
2.49 (1.32)
t(76) = 0.57, p = .57
CFQ
35
24.26 (12.72)
43
27.07 (11.56)
t(76) = -1.02, p = .31
GHQ
35
6.66 (4.62)
43
7.74 (4.90)
t(76) = -1.00, p = .32
*p< 0.05 level (2.tailed)
APT = Attention Process Training, BNT = Boston Naming Test, CFQ = Cognitive Failures
Questionnaire, COWA = Controlled Oral Word Association, CVLT = California Verbal Learning
Test, GHQ = General health Questionnaire, LD = Long Delay, LD Free = Long Delay Free Recall,
LM1 = Logical Memory 1, LM11 = Logical Memory 11, MCS = Mental Component Score, mRS
= Modified Rankin Scale, N = number, PCS = Physical Component Score, ROCF = Rey Osterreith
Complex Figure, sc = standard care, SD = Standard Deviation, ShD = Short Delay, SD Free =
Short Delay Free recall, SF-36 = Short Form Health Survey-36, VPA = Visual Paired Associates,
Pearson‟s bi-variate correlations were used to examine the relationships
between attention and all continuous variables (age, time since stroke, education,
Barthel Index and Mini Mental State Exam scores). Spearman‟s rank order
125
correlation was used to determine the relationship between attention and gender.
The correlations are presented in Table 10.
As can be seen in Table 10, there was no significant relationship between
age and any attention measure, however, time since stroke was significantly
related to all measures of the IVA-CPT except the Auditory Prudence score, and
both trials of the PASAT. Overall, the results show that the longer the time that
had elapsed since the stroke occurred, the better the performance was on attention
measures. There was a significant negative relationship between gender and the
2.0 second trial of the PASAT with females performing worse than males. On all
other measures gender was not a significant factor. There was also a significant
relationship between education and the Full Response and Auditory Prudence
scores of the IVA-CPT with higher levels of education relating to better scores on
those measures.
Functional independence, as measured by the Barthel Index, was
significantly related to increased attention as measured by the IVA-CPT Full
Attention Scale, the Visual Attention Scale and Bells Centre. An even stronger
relationship between the Barthel Index and Part A of the Trail Making Test, and
Bells Left and Right was revealed. These were all positive relationships with the
implication that higher scores on those measures of attention equates to a greater
level of functional independence. Scores on the MMSE were highly correlated
with four indices of the IVA-CPT as well as Bells Left and Right and TMT A.
That is, less cognitive impairment related to higher scores on those measures of
attention.
Given that multiple correlations were conducted a Bonferroni correction
was considered. The Bonferroni correction adjusts the alpha level by dividing .05
126
by the number of tests being conducted thereby minimising the likelihood of
finding a significant finding by chance. Therefore, the advantage of the
Bonferroni correction reduces the risk of Type 1 errors, i.e., erroneously
concluding the presence of a significant correlation; however, the disadvantage is
an increase in the risk of Type 2 errors. i.e., concluding the presence of a nonsignificant correlation. This disadvantage is a point of contention in the debate of
the use of the Bonferroni correction (Nakagawa, 2004). Therefore, given that the
correlations being looked at in this study were not primary outcomes and the
relationships were only points of interest, it was decided not to use the Bonferroni
correction.
Table 10
Correlations of demographic and functional variables with baseline measures of attention
Age
Time Since
Stroke
n = 79
Gender
Education
Barthel
MMSE
n = 87
n = 87
n = 87
n = 87
n = 87
IVA -CPT
FSAQ -.10
.14
.13
0.28*
0.23*
0.38**
AAQ
-.09
.17
.13
.17
0.25*
0.40**
VAQ
-.10
.12
.12
0.28*
0.22*
0.40**
FSRQ -.01
-.00
.09
0.25*
0.23*
0.29**
VPQ
.13
.02
.19
.09
0.17
0.26*
APQ
.06
.21
-.05
-.01
0.14
0.26*
TMT
A
-.01
.06
-.02
0.32**
0.28** 0.23*
B
-.03
-.07
.18
.27*
0.34**
0.24*
PASAT
2.4
.01
-.05
-.21
.07
.15
.03
2.0
.15
.19
.17
.17
.18
-0.32*
Bells
Left
-.06
.09
-.06
0.34**
0.36** 2.88**
Centre .08
.18
.01
.20
0.34**
0.26*
Right
.01
.02
-.01
0.30**
0.41** 0.37**
**p< 0.01 level (2-tailed)
*p< 0.05 level (2.tailed)
AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient, FSAQ = Full Scale
Attention Quotient FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and
Auditory Continuous Performance Test, N = Number, PASAT = Paced Auditory Serial Addition
Test, SC = Standard Care, SD = Standard Deviation, TMT = Trail Making Test, VAQ = Visual
Attention Quotient, VPQ= Visual Prudence Quotient.
As points of interest, further information for each ethnic group was
obtained. Unfortunately, statistical comparisons across the ethnic groups could
127
not be conducted to the widely varying sample sizes. In addition, analyses
examining ethnicity and stroke type could not be done due to low participant
numbers. However, to obtain an estimation of the severity of the stroke according
to ethnic group, the means and standard deviations each ethnic group produced on
the Mini Mental State Exam and the Barthel Index were generated, and these can
be seen in Table 11. These scores suggest that severity of stroke across each
ethnic group was similar. Also of interest was the performance of each ethnic
group on baseline measures of attention. The means and standard deviations for
those measures were obtained and are also included in Table 11. It can be seen
that overall the Pacific Island group performed worse on the IVA-CPT and TMT
compared to the other groups. This was followed by Pakeha then Maori and
finally Indian in that order. Performance on the fast trial of the PASAT was
uniform across groups although on the slower trial Maori and Pacific Island did
considerably worse than Pakeha and Indian who were relatively similar. Overall,
on the Bells Cancellation Test the Pakeha, Maori, and Pacific Island groups
performed similarly and the Indian group performed slightly better. However,
these observations were points of interest only and the causes for differences
between the ethnic groups may be the result of a number of factors such as stroke
location, severity of stroke, low SES, time since stroke, age or years of education
to name a few.
128
Table 11
Means and standard deviations of MMSE and BI measures and baseline attention measures according
to ethnicity.
Measure
Pakeha
Maori
Pacific Island
Indian
n
M (SD)
N
M (SD)
n M (SD)
n
M (SD)
MMSE
72
26.65 (2.71)
11 28.09 (1.51)
8 26.50 (2.67)
3
28.00 (1.00)
BI
45
14.67 (5.69)
11 13.18 (6.72)
8 15.50 (4.31)
3
16.33 (6.35)
IVA-CPT
FSAQ
65
-3.64 (3.31)
11 -2.75 (3.01)
8 -5.86 (3.59)
3
-1.47 (1.76)
AAQ
65
-3.17 (3.04)
11 -2.61 (2.58)
8 -4.44 (3.68)
3
-1.67 (1.59)
VAQ
65
-3.43 (3.54)
11 -2.65 (3.34)
8 -5.91 (4.29)
3
-1.50 (1.21)
FSRQ
65
-1.65 (3.32)
11 -0.69 (1.76)
8 -3.69 (4.86)
3
-0.60 (1.91)
APQ
65
-0.83 (2.93)
11 -0.06 (1.35)
8 -4.85 (5.29)
3
-1.67 (0.96)
VPQ
65
-0.90 (3.25)
11 -0.94 (2.27)
8 -5.31 (4.59)
3
-0.13 (1.21)
TMT
A
65
-2.58 (4.57)
9
-2.97 (4.64)
6 -4.89 (4.90)
2
0.90 (0.32)
B
54
-1.74 (2.45)
9
-4.29 (4.67)
6 -5.70 (3.63)
2
0.44 (0.32)
PASAT
2.4secs
37
-1.31(0.87)
8
-1.78 (0.53)
3 -1.61 (0.98)
3
-1.32 (0.88)
2.0secs
37
-0.90 (0.86)
8
-1.71 (1.22)
3 -1.85 (0.59)
3
-0.85 (0.70)
Bells
Left
69
12.67 (4.10)
11 11.73 (5.41)
8 11.13 (6.88)
3
14.67 (0.58)
Cntr
69
4.45 (1.13)
11 4.36 (1.50)
8 4.00 (1.77) 3
5.00 (.00)
Right
69
13.46 (2.58)
11 14.09 (2.70)
8 13.38 (3.46)
3
14.67 (0.58)
APT =Attention Process Training, AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient,
BI = Barthel Index, FSAQ = Full Scale Attention Quotient FSRQ = Full Scale Response Quotient,
IVA-CPT = Integrated Visual and Auditory Continuous Performance Test, MMSE = Mini Mental State Exam,
PASAT = Paced Auditory Serial Addition Test, SC = Standard Care, SD = Standard Deviation, TMT = Trail
Making Test, VAQ = Visual Attention Quotient, VPQ= Visual Prudence Quotient.
129
Another point of interest was the relationship between type of stroke and
baseline attention measures. As can be seen in Table 12 participants with POCS
performed the best on the FSAQ, the AAQ and the VAQ of the IVA-CPT
followed by participants with LACs. Participants with TACs, PACs and
haemorrhagic strokes performed the worst on those measures. On the FSRQ, the
APQ and the VPQ the POCs scores were a lot more uniform across all groups
although overall the participants in the POCs group again performed the best.
On the TMT A the TACs and PACs groups performed worse than the LACs
and POCs groups although the haemorrhagic group performed considerably worse
than all other groups. TMT B the LACs and POCs groups performed better than
the other groups. On both trials of the PASAT all groups were relatively similar
as was their performance on the three trials of the Bells Cancellation Test
although the LACs group did perform slightly better than the other four groups.
In summary, correlation analyses showed that the most number of
significant relationships with baseline attention measures was with time since
stroke followed by the MMSE, then the BI score, then education with finally just
one significant correlation with gender and age. Stroke severity seems similar
across the different ethnic groups. The means and standard deviations generated
for ethnicity and stroke type indicated differences in performance on attention
measure
130
Table 12
Ms and SDs of baseline attention measures for stroke type
Measure
TACs
PACs
LACs
POCs
Haemorrhagic
n
M (SD)
n
M (SD)
n
M (SD)
n
M (SD)
n
M (SD)
IVA-CPT
FSAQ
8 -3.83 (3.36) 30 -3.78 (3.29) 10 -2.49 (3.88) 7 -1.84 (2.07) 7
-3.56 (4.18)
AAQ
8 -3.60 (3.08) 30 -3.04 (2.85) 10 -2.56 (3.68)
7 -2.19 (2.63) 7
-2.97 (3.70)
VAQ
8 -3.70 (3.73) 30 -3.84 (3.55) 10 -2.34 (3.82) 7 -1.21 )1.42) 7
-3.11 (4.80)
FSRQ
8 -1.50 (2.93) 30 -1.69 (3.07) 10 -1.86 (3.61) 7 -0.51 (1.28) 7
-1.17 (4.60)
APQ
8 -4.38 (2.03) 30 -0.55 (2.67) 10 -2.24 (3.95) 7 0.56 (1.01) 7
-1.39 (4.12)
VPQ
8 -1.14 (2.81) 30 -1.51 (3.39) 10 -1.90 (3.46) 7 -0.17 (1.09) 7
-0.70 (4.19)
TMT
A
7 -2.67 (3.40) 31 -2.68 (5.26) 10 -1.13 (2.50) 5 -1.51 (1.58) 7
-4.57 (7.06)
B
5 -2.44 (2.45) 28 -2.07 (2.70) 10 -1.16 (1.44) 5 -1.54 (0.91) 6
-2.22 (4.08)
PASAT
2.4secs
4 -1.16 (1.01) 18 -1.09 (0.91) 7 -1.18 (0.46) 5 -1.47 (0.36) 5
-1.39 (0.91)
2.0secs
4 -0.74 (1.15) 18 -1.01 (1.17) 7 -0.79 (0.80) 5 -0.89 (0.49) 5
-1.17 (0.95)
Bells
Left
8 12.63 (3.20) 33 12.24 (4.63) 11 14.55 (0.52) 7 13.71 (2.98) 7
12.71 (5.62)
Centre
8 4.50 (1.41) 33 4.24 (1.48) 11 4.82 (0.41)
7 4.43 (0.79) 7
4.57 (0.79)
Right
8 10.75 (5.50) 33 14.00 (1.79 11 14.00 (1.00) 7 13.86 (2.61) 7
13.29 (3.73)
APT = Attention Process Training, AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient,
FSAQ = Full Scale Attention Quotient, FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and
Auditory Continuous Performance Test, LACS = Lacunar Stroke, PACS = Partial Anterior Circulation Stroke,
PASAT = Paced Auditory Serial Addition Test, POCS = Posterior Circulation Stroke, SC = Standard Care,
TACS = Total Anterior Circulation Strokes, TMT = Trail Making Test, VAQ = Visual Attention Quotient,
VPQ= Visual Prudence Quotient.
131
Correlations were also generated to investigate relationships between
baseline measures of attention and other neuropsychological measures. The
significant correlations presented in Table 13, all represent a positive direction
and signify that a higher score on the attention measure is indicative of a better
performance on the neuropsychological measure.
The majority of attention scores were significantly correlated to scores on
most trials of the Rey Osterreith Complex Figure, although for Bells (Left, Centre
and Right), the only other significant correlation was with the BNT. A large
number of the IVA-CPT scores correlated strongly with scores on Verbal Paired
Associates, particularly the Delayed Recall trial and also with a number of scores
on the CVLT. Scores on TMT B correlated strongly with almost all
neuropsychological measures except for Logical Memory (1 and 2) and COWA.
The 2.4 second trial of the PASAT had a strong positive correlation with all trials
of the Stroop while the 2.0 second trial of the PASAT, correlated positively with
the Word and Colour trials of the Stroop and all three trials of the CVLT. Of all
the other neuropsychological measures, only Logical Memory (both I and II) had
no relationship to any attention measure.
132
Table 13
Correlations between baseline measures of attention and other neuropsychological measures
Stroop
Measure
IVA-CPT
FSAQ
AAQ
VAQ
FSRQ
APQ
VPQ
TMT
A
B
PASAT
2.4
2.0
Bells
Left
Centre
Right
ROCF
Dot
Word
Colour
Copy
Short
Delay
n =58
n = 58
n = 58
n = 53
n = 52
.18
-.01
.32*
-.03
-.01
.11
.17
.10
.20
-.01
.03
.22
.09
-.05
.18
-.07
.04
.15
.27
.14
.35*
.28*
.15
.30*
.25
.36*
.23
.36*
.17
.45**
.41*
.31
.46**
.45**
.16
.23
.21
.16
.13
.19
Long
Delay
VPA
BNT
Recognition
Learning
Delay
Recall
n = 52
n = 52
n = 64
n = 63
.28*
.11
.40*
.26
.18
.42**
.27
.07
.40**
.28*
.19
.46**
.27
-.01
.34*
.35*
.01
.40
.25*
.24
.24
.18
.24
.22
.40**
.52**
.39**
.43**
.48**
.43**
.48**
.25
.58*
.68**
.36
.32
.24
.44*
.17
.37
-.04
-.09
-.03
.46*
.34*
.42*
.31*
ns
.34*
.46*
.35**
.39**
LM
COWA
CVLT
Short
Delay
Long
Delay
Short
Delay
Long
Delay
n = 65
n = 64
n = 64
n = 66
n = 68
n = 70
n = 70
.43*
.44*
.39**
.31*
.31*
.28
0.26*
.15
.34**
.27*
.23
.27*
.09
.19
.15
-.04
.16
.12
.10
.18
.21
.01
.16
.10
.10
.03
.11
.11
.06
.10
.21
.20
.30*
.20
.31**
.23
.23
.20
.31*
.19
.30*
.26*
.24*
.22
.29*
.05
.09
.05
.24
.54**
.19
.39**
.34**
.51**
.19
.22
.15
.16
.03
.22
.30*
.30*
.30*
.38**
.42**
.24
.11
.17
.49**
.49**
.30
.26
.18
.27
.05
.27
-.04
.14
.33*
.29
.27
.43**
.21
.41*
.41*
.34*
.37**
.28*
.16
-.04
-.11
-.08
-.03
-,09
.01
.26*
.31*
.37**
.02
.09
.10
.02
.08
.11
-.03
-.01\
-.01
.11
.07
.14
.10
.08
.11
.16
.13
.04
*p=<.05
** p=<.01
AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient, BNT = Boston Naming Test, COWAT = Controlled Oral Word Association Test,
CVLT = California Verbal Learning Test, FSAQ = Full Scale Attention Quotient FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and
Auditory Continuous Performance Test, LM = Logical Memory, N = Number, PASAT = Paced Auditory Serial Addition Test, SC = Standard Care, SD =
Standard Deviation, TMT = Trail Making Test, VAQ = Visual Attention Quotient, VPQ = Visual Prudence Quotient.
Recognition
133
Part 2: Analyses of Primary and Secondary Outcomes
The focus of Part 2 was to test the main study hypothesis (i.e. does APT
improve attention in acute stroke patients with attention deficit?). To examine the
effect of APT on attention deficit, a series of mixed 2 x 2 ANOVAs were conducted,
with a within subjects factor of time (pre- and post-intervention), and a between
subjects factor of treatment type (APT or standard care). Means and standard
deviations for attention measures and the SF36 for both the APT group and standard
care group at baseline and 5 weeks, are presented in Table 14 including the results of
the ANOVAs.
The results show that irrespective of the treatment provided between baseline
and 5 weeks, performance on the attention scores improved significantly as an effect
of time on the IVA-CPT, Full Scale Attention Quotient, Auditory Attention Quotient,
Visual Attention Quotient as well as the Full Scale Response Quotient. Significant
improvement over time was also demonstrated on other measures of attention
including both trials of the Trail Making Test, the 2.0 second interval trial of the
PASAT and the Bells left trial. There were no effects on any measures for group type
alone. There were, however, significant Group x Time interactions on the IVA-CPT
Full Scale Attention Score, Auditory Attention score and the Full Scale Response
score. (See Figure 8).
Repeated measures t-tests were used for post hoc analysis to look at changes
over time in the APT and standard care group separately for the Full Scale Attention
Score, Auditory Attention score and Full Scale Response Score. In these analyses,
the Bonferroni correction was used to adjust for multiple comparisons. Results of
these analyses showed that significant improvement for the APT group alone
134
occurred on all three measures. On the FSAQ the APT groups showed a significant
improvement from pre to post (t(27) = 6.14, p <.01). The APT group also improved
significantly on the AAQ (t(27) =-4.54, p <.01) and on the FSRQ (t(27)=-3.69,
p<.01).
There was no significant difference between the baseline and post-treatment
scores for the standard care group on any of these three measures. Figure 8 shows the
main findings for both the APT and the standard care group.
T-tests were then carried out to investigate whether or not there were any
significant differences between the means of the two groups for the IVA-CPT Full
Scale Attention score, the Auditory Attention score and the Full Scale Response score
at post-intervention. These analyses revealed there were no significant differences
between the groups on any of the three measures. In terms of the IVA-CPT Full
Scale score the results of the t-test suggest that the APT group made greater
improvement than their standard care group counterparts given that the APT group
was found to be significantly worse than the standard care group at baseline for this
measure.
There were no significant differences between baseline and post-intervention
measures on the secondary measure, the SF-36, as a result of time nor did time
interact with group. In summary, the analyses show an improvement on eight
measures of attention as an effect of time and significant improvement on three
quotients of the IVA-CPT as a result of Group x Time interactions although no
differences were detected on the secondary measure, the SF-36.
135
Table 14
Descriptive and inferential statistics showing significant results in bold
Baseline
Measures
APT
SC
of
Attention
M(SD)
M(SD)
IVA-CPT
FSAQ
-5.14 (3.69)
-3.23 (2.83)
AAQ
-4.17 (3.30)
-3.23 (2.60)
VAQ
-4.44 (4.07)
-3.01 (3.24)
FSRQ
-2.78(3.93)
-1.02(2.69)
APQ
-1.53(3.74)
-0.80(2.69)
VPQ
-1.87(4.05)
-0.83(2.60)
TMT
A
-2.91 (4.10)
-3.10 (4.80)
B
-2.28 (3.04)
-3.24 (4.01)
PASAT
2.4 secs
-1.49 (0.95)
-1.68 (0.55)
2.0 secs
-1.11 (0.83)
-1.51 (1.15)
Bells
Left
11.62 (5.02)
12.49 (4.62)
Centre
4.34 (1.17)
4.34 (1.39)
Right
13.55 (2.96)
13.40 (2.91)
SF-36
MCS
45.56 (11.47)
43.11(11.34)
**Significant at the 0.01 level (2-tailed)
*Significant at the 0.05 level (2.tailed)
ANOVA
Results Main
Effect
Time
Post APT
Main effect
Group
Interaction (Time
x Group)
Average
APT
M(SD)
M(SD)
SC
M(SD)
Average
M(SD)
-4.13 (3.38)
-3.68 (2.96)
-3.69 (3.70)
-1.85(3.42)
-1.14(3.22)
-1.32(3.38)
-2.26 (3.35)
-1.75 (2.15)
-2.75 (3.91)
-0.31(2.30)
-0.54(2.17)
-0.78(3.38)
-2.90 (3.35)
-2.58 (3.07)
-2.66 (3.39)
-0.62(3.42)
-0.80(3.22)
0.92(3.38)
-2.59 (3.34)
-2.19 (2.69)
-2.71 (3.61)
-0.47(2.92)
-0.45(2.77)
-0.85(3.35)
F(1,57)=20.94**
F(1,57)=17.88**
F(1,57)=7.15**
F(1,57)=8.84**
F(1,57)=2.21
F(1,57)=0.88
F(1,57)=0.65
F(1,57)=0.01
F(1,57)=0.76
F(1,57)=1.21
F(1,57)=0.01
F(1,57)=0.42
F(1,57)=13.24**
F(1,57)=5.97*
F(1,57)=3.13
F(1,57)=4.60*
F(1,57)=2.23
F(1,57)=1.23
-3.01 (4.44)
-2.81 (3.61)
-1.62 (3.60)
-1.10 (3.10)
-1.67 (2.96)
-1.68 (2.26)
-1.65 (3.25)
-1.42 (2.65)
F(1,53)=11.04**
F(1,43)=12.35**
F(1,53)=0.01
F(1,43)=0.79
F(1,53)=0.03
F(1,43)=0.23
-1.58 (0.78)
-1.30 (1.00)
-1.11 (1.01)
-0.39 (0.96)
-1.73 (0.75)
-1.31 (0.89)
-0.82 (1.02)
-0.82 (1.02)
F(1,26)=1.66
F(1,26)=8.54**
F(1,26)=1.88
F(1,26)=4.13
F(1.26)=2.80
F(1,26)=2.67
12.09 (4.78)
4.34 (1.29)
13.47 (2.91)
12.79 (2.70)
4.48 (0.78)
13.76 (1.70)
12.74 (4.05)
4.66 (0.87)
14.14 (1.81)
12.77 (3.48)
4.58 (0.83)
13.97 (1.76)
F(1,62)=4.87*
F(1,62) =2.42
F(1,62) =2.18
F(1,62)=0.16
F(1.62)=0.14
F(1,62)=0.05
F(1,62)=2.00
F(1.62)=0.37
F(1,62)=0.69
44.28(11.39)
45.58(11.47)
46.30(10.23)
45.95 (9.47)
F(1,65)=1.37
F(1,65)=0.16
F(1,65)=1.34
AAQ = Auditory Attention Quotient, ANOVA = analysis of variance, APQ = Auditory Prudence Quotient, APT = Attention Process Training, FSAQ = Full Scale Attention
Quotient, FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and Auditory Continuous Performance Test, MCS= Mental Component Score, PASAT= Paced
Auditory Serial Addition Task, PCS= Physical Component Score, SC = Standard Care, SF-36 = Short Form Health Survey-36, TMT= Trail Making Test, VAQ = Visual Attention
Quotient, VPQ = Visual Prudence Quotient
136
Figure 8. The effects of APT on IVA-CPT measures. Data presented as means
and standard deviations.
Part 3: Analysis of qualitative data
Although the means of baseline measures were similar across the two
groups it was also of interest to look at the distribution of participants from each
group into qualitative descriptive categories. Qualitative descriptive terms are
commonly used in clinical practice (Lezak, 2004) to describe performance,
providing further clarity and understanding of an obtained numerical score. In
this study the range of z-scores were classified into seven distinct qualitative
groups according to the number of standard deviations from the mean as follows:
<-3 SDs = Very impaired, ≥-3 to <-2= Impaired, >-2 to <-1=Below Average, >-1
to <1=Average, >1 to <2= Above Average, >2 to <3=Superior and >3=Very
Superior (Spreen & Strauss, 1998; Strauss, Sherman & Spreen, 2006). However,
scores on the Bells test were not converted to z-scores therefore participants were
137
grouped according to the actual number of bells (0, 1, 2, 3, or >3), missed on each
trial. The number of participants in each group is presented in percentages.
Table 15 provides a summary of the proportion of individuals in each group
(APT and SC) whose z-scores fell into each qualitative category for each measure
of attention. Table 16 provides a summary of the proportion of individuals in
each group (APT and standard care) whose z-scores fell into each qualitative
category on the other neuropsychological measures of executive functioning,
memory and language.
As seen in Table 15, a large proportion of participants in both the APT and
standard care groups had poor attention abilities as evidenced by the number of
participants who obtained scores in the impaired ranges on the Full Attention,
Auditory Attention and Visual Attention scores of the IVA CPT, with the largest
percentage of these scores falling in the very impaired range. Only one
participant obtained a score that placed him/her above the average range. Scores
on the IVA-CPT Full Response were relatively evenly distributed across ranges
although there were more scores in the very impaired range for the APT group
than the standard care group. Scores on the IVA-CPT Auditory Prudence were
also more evenly distributed with most scores falling in the average range. Both
groups were similar in their distribution of scores. On IVA-CPT Visual Prudence,
while a large percentage of scores fell in the impaired range, there were also more
scores falling in the superior range. However, again the distribution of scores in
both groups was similar. On the Trail Making Test, Part A and B, all scores on
this task fell within the very impaired to average range with no scores reaching the
above average range. On Part B of the TMT there were more participants from
the standard care group in the very impaired range compared to the APT group.
138
On the PASAT, there were fewer scores at either end of the range and is likely
attributable to fewer participants completing this task. Only 28 participants were
able to complete the 2.0 sec trial and 38 participants completed the 2.4 sec trial.
On the Bells test the majority of participants from both groups circled all the bells.
139
Table15
Proportion of participants in each qualitative category on measures of attention
z-score ranges
≥-3 to <-2
< -3
Measures of
Attention
IVA-CPT
FSAQ
AAQ
VAQ
FSRQ
APQ
VPQ
TMT
A
B
PASAT
24
20
Very impaired
APT
SC
n (%)
n (%)
APT
n (%)
Impaired
SC
n (%)
24 (68.6)
19 (54.3)
19 (54.3)
13 (37.1)
7 (20.0)
10 (28.6)
19 (44.2)
19 (44.2)
13 (30.2)
6 (14.0)
7 (16.3)
7(16.3)
3 (8.6)
4 (11.4)
4 (11.4)
4 (11.4)
3 (8.6)
1 (2.9)
8 (22.9)
5 (14.3)
13 (30.2)
12 (27.9)
0
0
0
1 (2.3)
APT
28.8
2.9
11.6
APT
n (%)
5(11.6)
3 (7.0)
11 (25.6)
8 (18.6)
2 (4.7)
3 (7.0)
4 (11.4)
6 (17.1)
3 (8.6)
3 (8.6)
1 (2.9)
4 (11.4)
7 (16.3)
11 (25.6)
7 (16.3)
5 (11.6)
4 (9.3)
4 (9.3)
3 (8.6)
4 (11.4)
8 (22.9)
10 (28.6)
16 (45.7)
14 (40.0)
5 (14.3)
4 (11.4)
4 (9.3)
4 (9.3)
4 (11.4)
4 (11.4)
5 (11.6)
6 (14.0)
6 (17.1)
4 (11.4)
5 (11.6)
4 (9.3)
10 (28.6)
8 (22.9)
13 (30.2)
4 (9.3)
3
SC
13.9
9.3
13.9
≥-1 to <1
Below Average
APT
SC
n (%)
n (%)
>3
Bells-raw score*
Left
Centre
Right
≥-2 to <-1
APT
5.7
2.9
2.9
≥ 1 to <2
Average
SC
n (%)
≥2 to <3
Above Average
APT
SC
n (%)
n (%)
Superior
APT
SC
n (%)
n (%)
9 (20.9)
7 (16.3)
9 (20.9)
15 (34.9)
19 (44.2)
16 (37.2)
0
1 (2.9)
0
3 (8.6)
7 (20.0)
3 (8.6)
0
0
0
4 (9.3)
7 (16.3)
8 (18.6)
0
0
0
1 (2.9)
0
2 (5.7)
0
0
0
2 (4.7)
1 (2.3)
2 (4.7)
11 (31.4)
9 (25.7)
16 (37.2)
11 (25.6)
0
0
0
0
0
0
0
0
2 (5.7)
7 (20.0)
2 (4.7)
11(25.6)
1 (2.9)
0
0
0
0
0
0
0
% with specified number of Bells missed
2
SC
APT
SC
APT
7.0
2.9
9.3
14.3
2.3
11.4
0
20.0
4.7
5.7
11.6
22.9
1
0
SC
20.9
16.3
23.3
APT
40.0
54.3
48.6
APT = Attention Process Training, AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient, FSAQ = Full Scale Attention
Quotient, FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and Auditory Continuous Performance Test, PASAT = Paced
Auditory Serial Addition Test, SC = Standard Care, SD = Standard Deviation, TMT = Trail Making Test, VAQ = Visual Attention Quotient, VPQ=
Visual Prudence Quotient
*Bell scores are not converted to z-scores
SC
48.8
72.1
46.5
140
Table 16
Proportion of participants in each qualitative category on measures of executive functioning, language and memory
z-score ranges
≥-3 to <-2
< -3
Very impaired
APT
SC
n (%)*
n (%)
APT
n (%)
Impaired
SC
n (%)
≥-2 to <-1
Below Average
APT
SC
n (%)
n (%)
≥-1 to <1
APT
n (%)
Average
SC
n (%)
≥ 1 to <2
Above Average
APT
SC
n (%)
n (%)
≥2 to <3
Superior
APT
SC
n (%)
n (%)
Measure
Stroop
Dot
8 (22.9)
10 (23.3) 3 (8.6)
1 (2.3)
1 (2.9)
6 (14.0)
14 (40.0) 16 (37.2) 1 (2.9)
1 (2.3)
0
0
Word
8 (22.9)
11 (25.6) 1 (2.9)
6 (14.0)
4 (11.4)
3 (7.0)
14 (40.0) 13 (30.2) 0
1 (2.3)
0
0
Colour
3 (8.6)
4 (9.3)
3 (8.6)
2 (4.7)
3 (8.6)
5 (11.6)
16 (45.7) 20 (46.5) 2 (5.7)
3 (7.0)
0
0
ROCF
Copy
8 (22.9)
12 (27.9) 2 ( 5.7) 4 (9.3)
2 (5.7)
3 (7.0)
12 (34.3) 12 (27.9) 0
2 (4.7)
0
0
ShD
3 (8.6)
1 (2.3)
1 (2.9)
5 (11.6)
6 (17.1)
10 (23.3) 11 (31.4) 7 (16.3)
2(5.7)
7 (16.3)
1 (2.9)
2 (4.7)
LD
4 (11.4)
3 (7.0)
4 14.3) 3 (7.0)
2 (5.7)
9 (20.9)
9 (25.7)
7 (16.3)
3 (8.6)
7 (16.3)
1 (2.9)
2 (4.7)
Rec
4 (11.4)
5 (11.6)
6 (17.1) 8 (18.6)
5 (14.3)
5 (11.6)
7 (20.0)
10 (23.3) 2 (5.7)
1 (2.3)
0
2 (4.7)
VPA
1
0
0
0
4 (9.3)
5 (14.3)
10 (23.3) 21 (60.0) 18 (41.9) 4 (11.4) 4(9.3)
0
0
2
2
0
0
0
1 (2.3)
9 (25.7)
11 (25.6) 21 (60.0) 15 (34.9) 0
8 (18.6)
0
0
BNT
5 (14.3)
3 (7.0)
5 (14.3) 5 (11.6)
4 (11.4)
4 (9.3)
15 (42.9) 20 (46.5) 3 (8.6)
4 (9.3)
0
0
LM 1
0
0
0
1 (2.3)
3 (8.6)
5 (11.6)
22 (62.9) 21 (48.8) 5 (14.3) 5 (11.6)
2 (5.7)
2 (4.7)
LM 2
0
0
1 (2.9)
0
2 (5.7)
4 (9.3)
21 (60.0) 18 (41.9) 6 (17.1) 10 (23.3) 2 (5.7)
2 (4.7)
COWA
0
1 (2.3)
5 (14.3) 6 (14.0)
13 (37.1) 10 (23.3) 13 (37.1) 19 (44.2) 0
2 (4.7)
0
0
CVLT
ShD Free
1 (2.9)
2 (4.7)
3 (8.6)
6 (14.0)
7 (20.0)
4 (9.3)
17(48.6)
22 (51.2) 5 (14.3) 4 (9.3)
0
0
ShD Cued
1 (2.9)
4 (9.3)
6 (17.1) 3 (7.0)
5 (14.3)
10 (23.3) 18 (51.4) 18 (41.9) 2 (5.7)
5 (11.6)
1(2.9)
0
LD Free
1 (2.9)
2 (4.7)
2 (5.7)
7 (16.3)
8 (22.9)
7 (16.3)
19 (54.3) 21 (48.8) 3 (8.6)
2 (4.7)
0
1 (2.3)
LD Cued
1 (2.9)
4 (9.3)
4 (11.4) 4 (9.3)
9 (25.7)
5 (11.6)
17 (48.6) 24 (55.8) 1 (2.9)
3 (7.0)
1(2.9)
0
Recognition 5 (14.3)
1 (2.3)
5 (14.3) 4 (9.3)
7 (20.0)
5 (11.6)
15 (42.9) 24 (55.8) 1 (2.9)
6 (14.0)
0
0
APT = Attention Process Training, BNT, Boston Naming Test, COWA = Controlled Oral Word Association, CVLT = California Verbal learning Test, LD Cued =
Long Delay Cued, LD Free = Long Delay Free, LM = Logical Memory, ROCF = Rey Osterreith Complex Figure, SC = Standard Care, VPA = Visual Paired Associates
141
As can be seen in Table 16, generally, the greater proportion of scores for
each neuropsychological measure fell within the average range. Those which
were not in the average range tended to fall below the average range while very
few were above the average range. On the Stroop Test, most performances were
spread across all ranges although no scores reached the superior range. The
largest proportion of participants on this task produced scores that fell within the
average range with the next largest group performing in the very impaired range.
The APT and standard care groups had similar distributions across most ranges
for each trial although the APT group had more participants in the impaired range
and the below average range for Stroop Word and Stroop Dot respectively,
compared to the standard care group.
On some measures a small number of participants scored in the superior
range. This was noted on the short delay and long delay trial of the ROCF,
Logical Memory 1 and 2, the short and long delay cued recall and long delay free
recall of the CVLT. No participants fell in the very impaired range on both Verbal
Paired Associates 1 and 2 or the Logical Memory test 1 and 2 and only one
participant from both groups obtained a score that fell in the impaired range for
both Logical Memory 1 and 2. However, an equal number of participants from
both groups reached the superior range for Logical Memory 1 and 2. These
results indicate that the two groups were quite similar on these two measures.
Indeed, an overview of all the scores of neuropsychological measures, indicate
that overall, the APT and standard care groups were comprised of participants
with similar distribution of abilities. This finding is consistent with the results of
the earlier analysis when t-tests were conducted to compare performance of
baseline neuropsychological measures between the two groups (See Table 9).
142
Changes in qualitative ranges from pre to post-intervention
In order to track movement across qualitative categories, Table 17 shows
the proportion of people in each qualitative category for attention measures at
baseline and post-intervention for the APT group. It can be seen that there has
been considerable changes in the number of participants falling into each category
on most measures. On all indices of the IVA-CPT, there was a considerable
reduction in the number of participants in the very impaired range at the postintervention measure compared to baseline. As a consequence of this change an
increase in the number of participants falling in the average, above average, and
superior ranges at post-intervention, was observed. These changes reflect the
main effect of improvement over time as shown by the results of the ANOVAs in
Part 2 of this chapter.
On TMT A, there was a general improvement across all categories as seen
by the reduction in the number of participants falling in the below average,
impaired and very impaired ranges and an increase in those numbers falling in the
average and above average range. On both TMT A and B there was a notable
increase in the number of participants in the average range at post-APT. On both
trials of the PASAT, there were fewer participants in the below average and
impaired range at post-APT and there was an increase in the number of
participants in the average range and above average range.
On Bells Left and Bells Centre, there was a reduction in the number of
participants who missed more than 3 bells over time and a significant increase in
the number of participants who only missed 2 bells on Bells Left. On Bells Right
there was also a significant increase in the number of participants who only
missed 2 bells.
143
Table 17
Changes across qualitative categories by the APT group from baseline to post-intervention. Data presented as percent of participants who fell within each
category at baseline and post-intervention.
z-score range
≥-3 to <-2
< -3
Measure
IVA-CPT
FSAQ
AAQ
VAQ
FSRQ
APQ
VPQ
Trails
A
B
PASAT
24
20
≥-1 to <1
≥ 1 to <2
≥2 to <3
Very impaired
Baseline Post
n (%)
n (%)
Impaired
Baseline Post
n (%)
n (%)
Below Average
Baseline Post
n (%)
n (%)
Average
Baseline
Post
n (%)
n (%)
Above Average
Baseline Post
n (%)
n (%)
Superior
Baseline Post
n (%)
n (%)
24 (68.6)
19 (54.3)
19 (54.3)
13 (37.1)
7 (20.0)
10 (28.6)
10 (28.6)
7 (20.0)
9 (25.7)
2 (5.7)
1 (2.9)
3 (8.6)
3 (8.6)
4 (11.4)
4 (11.4)
4 (11.4)
3 (8.6)
1 (2.9)
4 (11.4)
7 (20.0)
3 (8.6)
1 (2.9)
0
0
4 (11.4)
6 (17.1)
3 (8.6)
3 (8.6)
1 (2.9)
4 (11.4)
4 (11.4)
5 (14.3)
5 (14.3)
4 (11.4)
4 (11.4)
4 (11.4)
3 (8.6)
4 (11.4)
8 (22.9)
10 (28.6)
16 (45.7)
14 (40.0)
7 (20.0)
7 (20.0)
9 (25.7)
15 (42.9)
17 (48.6)
16 (45.7)
0
1 (2.9)
0
3 (8.6)
7 (20.0)
3 (8.6)
4 (11.4)
2 (5.7)
3 (8.6)
6 (17.1)
7 (20.0)
6 (17.1)
0
0
0
1 (2.9)
0
2 (5.7)
0
1 (2.9)
0
1 (2.9)
0
0
8 (22.9)
5 (14.3)
7 (20.0)
6 (17.1)
5 (14.3)
4 (11.4)
1 (2.9)
2 (5.7)
4 (11.4)
4 (11.4)
3 (8.6)
4 (11.4)
11 (31.4)
9 (25.7)
19 (54.3)
16 (45.7)
0
0
1 (2.9)
0
0
0
0
0
0
0
0
0
6(17.1)
4 (11.4)
3(8.6)
1 (2.9)
10(28.6)
8 (22.9)
8(22.9)
2 (5.7)
2(5.7)
7 (20.0)
7(20.0)
14 (40.0)
1(2.9)
0
1(2.9)
2 (5.7)
0
0
0
0
>3
Bells-raw score *
Left
Centre
Right
≥-2 to <-1
3
Baseline
Post
Baseline
28.8
2.9
11.6
22.6
0
14.4
5.7
2.9
2.9
% with specified number of Bells missed
2
Post
Baseline
Post
Baseline
5.7
2.9
2.9
2.9
11.4
5.7
20.0
8.6
14.3
14.3
20.0
22.9
1
0
Post
Baseline
Post
25.7
25.7
20.0
40.0
54.3
48.6
17.1
51.4
37.1
APT = Attention Process Training, AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient, FSAQ = Full Scale Attention Quotient,
FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and Auditory Continuous Performance Test, N = Number, PASAT= Paced Auditory
Serial Addition Test, TMT= Trail Making Test, VAQ = Visual Attention Quotient, VPQ = Visual Prudence Quotient..
*Bell scores are not converted to z-scores
144
Table 18 presents the qualitative categories for the z-scores obtained by the
standard care group at baseline and at post-intervention. There was a reduction in
the number of participants in the below average, impaired and very impaired
range from pre to post-intervention on all but one index of the IVA-CPT. It can
also be seen that on the Full Scale Attention, Auditory Attention and Visual
Attention indices, there was an increase in the number of participants reaching the
average range and above average range. On the Full Scale Response Index there
was an increase in the number of participants in the above average range and one
participant in the very superior range at the post-intervention stage. On both trials
of the TMT there were fewer participants falling in the very impaired range at
post-intervention compared to baseline. Also on both trials of the TMT, there was
an increase in the number of participants in the above average range. On the Bells
test there was a reduction in the number of participants who missed more than 3
bells on Bells Centre and Bells Right.
Figure 9 shows the changes in categories from baseline to post-treatment for
both groups for the main findings. Figure 10, shows category changes from
baseline to post-treatment for both groups on all scores of the IVA-CPT. It can be
seen that although participants from both groups moved out of the very impaired
range on all indices of the IVA-CPT, the percentage of participants that moved
was considerably greater for the APT group. Overall, there was more movement
into the higher ranges from the APT group although only one participant (from
the standard care group) managed to reach the very superior range (Full
Response) at post-intervention. It can be seen in Figure 11 that on both trials of
the PASAT there were significant positive shifts for participants in the APT group
compared to the standard care group where relatively little change over time
145
occurred. Interestingly, as seen in Figure 12 there was no change in either group
for the percentage of participants who missed three bells on all three trials.
Figure 9. Bar graph showing the category changes from baseline to post-treatment
for the main findings for both the APT and standard care group
146
Table 18
Changes across qualitative categories by the SC group from baseline to post-intervention. Data presented as percent of participants who fell within each category at baseline and
post-intervention
z-score range
≥-3 to <-2
< -3
Measure
IVA-CPT
FSAQ
AAQ
VAQ
FSRQ
APQ
VPQ
TMT
A
B
PASAT
24
20
≥-1 to <1
≥ 1 to <2
≥2 to <3
>3
Very impaired
Baseline
Post
n (%)
n (%)
Impaired
Baseline
Post
n(%)
n (%)
Below Average
Baseline
Post
n (%)
n (%)
Average
Baseline
Post
n (%)
n (%)
Above Average
Baseline
Post
n (%)
n (%)
Superior
Baseline
Post
n (%)
n (%)
V Superior
Baseline
Post
n (%)
n (%)
19 (44.2)
19 (44.2)
13 (30.2)
6 (14.0)
7 (16.3)
7(16.3)
12 (27.9)
10 (23.3)
11 (25.6)
4 (9.3)
4 (9.3)
6 (14.0)
5(11.6)
3 (7.0)
11 (25.6)
8 (18.6)
2 (4.7)
3 (7.0)
3(7.0)
5 (11.6)
2 (4.7)
1 (2.3)
2 (4.7)
2(4.7)
7 (16.3)
11 (25.6)
7 (16.3)
5 (11.6)
4 (9.3)
4 (9.3)
5 (11.6)
5 (11.6)
6 (14.0)
5 (11.6)
2 (4.7)
2 (4.7)
9 (20.9)
7 (16.3)
9 (20.9)
15 (34.9)
19 (44.2)
16 (37.2)
11 (25.6)
11 (25.6
12 (27.9)
12 (27.9)
15 (34.9)
14 (32.6)
0
0
0
4 (9.3)
7 (16.3)
8 (18.6)
1 (2.3)
1 (2.3)
1 (2.3)
8 (18.6)
9 (20.9)
8 (18.6)
0
0
0
2 (4.7)
1 (2.3)
2 (4.7)
0
0
0
1 (2.3)
0
0
0
0
0
0
0
0
0
0
0
1 (2.3)
0
0
13 (30.2)
12 (27.9)
8 (18.6)
8 (18.6)
4 (9.3)
4 (9.3)
2 (4.7)
6 (14.0)
5 (11.6)
6 (14.0)
3 (7.0)
2 (4.7)
16 (37.2)
11 (25.6)
16 (37.2)
14 (32.6)
0
0
3 (7.0)
1 (2.3)
0
0
0
0
0
0
0
0
0
1 (2.3)
0
0
5 (11.6)
4 (9.3)
7 (16.3)
6 (14.0)
13 (30.2)
4 (9.3)
11 (25.6)
6 (14.0)
2 (4.7)
11(25.6)
2 (4.7)
8 (18.6)
0
0
0
0
0
0
0
0
0
0
0
0
>3
Bells
Left
Centre
Right
≥-2 to <-1
3
Baseline
Post
Baseline
Post
13.9
9.3
13.9
13.9
2.3
2.3
7.0
2.3
4.7
7.0
2.3
4.7
% with specified number of Bells missed
2
Baseline
Post
9.3
0
11.6
7.0
0
7.0
1
0
Baseline
Post
Baseline
Post
20.9
16.3
23.3
23.3
11.6
18.6
48.8
72.1
46.5
34.9
65.1
48.8
APT = Attention Process Training, AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient, FSAQ = Full Scale Attention Quotient, FSRQ =
Full Scale Response Quotient, IVA-CPT = Integrated Visual and Auditory Continuous Performance Test, N = Number, PASAT= Paced Auditory Serial Addition
Task, TMT= Trail Making Test, VAQ = Visual Attention Quotient, VP = Visual Prudence.
*Bell scores are not converted to z-scores
147
Figure 10. Comparison of the categories moved from pre to post-treatment for all scores of the IVA-CPT
for both APT and Standard Care groups.
148
Figure 11. Comparison of the categories moved from pre to post-treatment for scores of the TMT Part A & B and
PASAT 2.4 and 2.0 trials for both APT and Standard Care groups
149
Figure 12. Comparison of the categories moved from pre to post-treatment for
scores on the Bells Cancellation Test for both APT and Standard Care groups.
Also of interest to this study were the actual number of categories moved
from baseline to post-intervention for participants in both APT and standard care
groups. This data provided a clinical perspective of how the participants had
improved. The means and standard deviations of the number of categories each
group had moved are presented in Table 19. T-tests were conducted on this data
in order to determine if either group had moved significantly more than the other
group on any measure. The data shows that the Full Scale Attention Quotient was
the only measure for which a significant difference in performance between the
two groups was found, with the improvement in category changes made by the
APT group from baseline to post-intervention, being significantly greater than the
standard care group. At baseline the APT group was significantly worse than the
standard care group on this measure and as such there was a lot more recovery of
function for the APT group to achieve before a ceiling affect was reached. This
result is consistent with the significant improvement as revealed by the ANOVA
in the previous section.
150
Table 19
Ms and SDs of number of categories of change from baseline to post-intervention for both APT
and SC groups.
Measure
IVA-CPT
FSAQ
AAQ
VAQ
FSRQ
APQ
VPQ
TMT
A
B
PASAT
2.4
2.0
APT
M (SD)
SC
M (SD)
t-test
0.96 (1.17)
0.82 (1.19)
0.54 (1.35)
1.25 (1.51)
0.64 (1.31)
1.57 (1.35)
0.29 (0.97)
0.52 (1.21)
0.32 (1.05)
0.48 (1.75)
0.16 (1.86)
1.23 (1.45)
t(57) = 2.41, p = 0 .02*
t(57) = 0.98, p = 0.33
t(57) = 0.68, p = 0.50
t(57) = 1.80, p = 0.08
t(57) = 1.14, p = 0.26
t(57) = 0.95, p = 0.35
0.69 (1.26)
0.55 (1.36)
0.41 (0.91)
0.48 (1.05)
t(53) = 0.95, p = 0.35
t(53) = 0.20, p = 0.85
0.27 (0.70)
0.87 (0.64)
0.00 (0.71)
0.38 (0.77)
t(26) = 1.00, p = 0.33
t(26) = 1.81, p = 0.08
Bells
Left
-1.17 (3.48)
-0.26 (1.48)
t(62) = -1.41, p = 0.16
Centre
-0.17 (1.10)
-0.31 (1.18)
t(62) = 0.49, p = 0.62
Right
-0.21 (2.76)
-0.74 (2.39)
t(62) = 0.83, p = 0.41
*p = <.05
AAQ = Auditory Attention Quotient, APQ = Auditory Prudence Quotient, FSAQ = Full Scale
Attention Quotient, FSRQ = Full Scale Response Quotient, IVA-CPT = Integrated Visual and
Auditory Continuous Performance Test, PASAT= Paced Auditory Serial Addition Task, TMT=
Trail Making Test, VAQ = Visual Attention Quotient, VPQ = Visual Prudence Quotient.
Part 4: Factors influencing progress through APT
To complete the analyses, a series of correlations were conducted in order to
investigate if any participant characteristics influenced performance on APT.
Baseline demographics, performance on the attention measures and other
neuropsychological measures were correlated with progression through the APT
tasks as well and the total number of hours each participant completed.
Correlations were used to determine whether participants‟ demographics of
interest and their performances on all neuropsychological measures at baseline
related to how far they had progressed on tasks of APT. Pearson‟s bi-variate
correlations were used for continuous variables. The PASAT 2.4sec trial
correlated with reaching a higher auditory task (r = .48, p <0.05) as did the
PASAT 2.0 sec trial (r =.57, p <.05). Bells Right also correlated with reaching a
151
higher visual task (r = .43, p <.05). There were no significant relationships
between any other measure and the highest auditory or visual task reached. Of the
demographic information no variable correlated significantly with the highest
auditory or visual task (See Appendix E for the table of correlations). Statistical
comparisons for ethnicity and stroke type could not be done due to low participant
numbers. Therefore, the means and standards for ethnicity and stroke type for the
highest tasks that were reached in both modalities of APT were generated and are
presented in Table 20. Stroke severity as measured by scores on the MMSE and
BI did not appear to differ between ethnic groups however despite this, it can be
seen that the Pakeha group progressed considerably further than the other three
groups on the auditory tasks. They were followed by the Pacific Island and Indian
Groups whose progression through the tasks was similar. The Maori group made
the least progression on auditory tasks. On the visual tasks the Pakeha group again
made the most progress followed by the Pacific Island group. The Maori and
Indian participants did not complete a visual task.
Also in Table 20, it can be seen that of the known stroke types, the PACs
group made the most progress on the auditory tasks followed by the TACs, POCs
and Haemorrhagic groups which were similar. The LACs group made the least
progress on the auditory tasks. However on the visual tasks the TACs group made
considerably further progress than the other groups followed by the PACs group.
The POCs and Haemorrhagic groups made considerably less progress on the
visual tasks. The lacunar stroke participant did not complete any visual task.
152
Table 20
Ms and SDs of ethnicity and stroke type for total highest auditory and visual task reached
Highest auditory task reached
Highest visual task reached
n
M
SD
M
SD
Ethnicity
Pakeha
28
52.86
30.52
26.21
29.53
Maori
2
11.50
16.26
.00
.00
Pacific Island
4
24.00
25.78
8.25
16.5
Indian
1
24.00
.00
Stroke Type
TACS
4
42.33
32.62
49.67
59.77
PACS
12
58.00
32.77
26.16
32.71
LACS
1
20.00
.00
POCS
2
31.00
9.90
16.50
23.33
Haemorrhagic
5
33.60
26.95
19.80
18.07
Unknown
10
43.60
26.09
16.50
17.40
APT = Attention Process Training, LACS = Lacunar Stroke, PACS = Partial Anterior Circulation
Stroke, POCS = Posterior Circulation Stroke, TACS = Total Anterior Circulation Strokes.
Of the 35 participants randomised to the APT group, only 5 participants
completed the full 30 hours; 17 participants completed 15 or more hours (i.e., half
of the scheduled intervention), and on average each participant received 15.92
hours. Pearson‟s correlations looking at the relationships between baseline
demographics, measures of attention and other neuropsychological measures and
the total number of hours of APT completed, were also conducted. (See
Appendix F for table of correlations). On measures of attention there was a
significant positive relationship between the Auditory Prudence score and the total
number of hours completed (r = .409, p =.05) meaning a better Auditory Prudence
score was associated with more hours of APT being completed. There was also a
positive significant relationship between the score on the MMSE and the total
number of hours completed (r = .401, p = .05). This meant that a higher score on
the MMSE was related to more hours of APT being completed. Statistical
comparisons for ethnicity and stroke type could not be done because of the low
participant numbers. As seen in Table 21 means and standards were generated for
ethnicity and stroke type for the number of APT hours completed.
153
Table 21
Ms and SDs for ethnicity and stroke type for the mean number of hours of APT
Completed.
Hours of APT
n
mean
sd
Ethnicity
Pakeha
28
17.60
9.57
Maori
2
9.75
9.55
Pacific Islander
4
8.75
4.97
Indian
1
10.00
Stroke Type
9.30
TACS
3
22.3
8.44
PACS
12
17.88
LACS
1
1.50
2.83
POCS
2
8.00
8.5
Haemorrhagic
5
17.20
9.45
Unknown
10
14.15
APT = Attention Process Training, LACS = Lacunar Stroke, PACS = Partial Anterior Circulation
Stroke, POCS = Posterior Circulation Stroke, TACS = Total Anterior Circulation Strokes.
Finally, correlations were conducted between post-intervention attention
scores and the highest tasks reached in both auditory and visual modalities (See
Appendix E), and between post-intervention scores and the total number of hours
of APT received. (See Appendix F). Neither set of correlations revealed any
significant relationship between those variables.
In summary, there was no evidence that progression through APT in this
study was influenced by participants‟ baseline demographics and only minimal
evidence that participant‟s ability on baseline neuropsychological measures
affected how far the participants progressed on APT. The extent to which the
participants progressed on APT tasks in both modalities was not associated with
outcome measures. A comparison between demographics, neuropsychological
measures and the number of APT hours received, revealed a positive relationship
between one baseline attention measure and the MMSE with more hours.
However the amount of intervention received was not associated with outcome
measures.
154
Chapter 6: Discussion
The evidence for the effectiveness of cognitive rehabilitation following
neurological damage has grown steadily in the last decade amidst an environment
that has historically been and indeed remains dominated by a focus on functional
rehabilitation (Giles, 2010; Mok et al., 2004). Although much of the evidence for
cognitive rehabilitation focuses on patients who have suffered a TBI (Carney et
al., 1999; Cicerone et al., 2000; Park & Ingles, 2001; Prigatano, 1986; Wilson &
Moffat, 1992) there is also significant interest in adopting this approach with
stroke patients, a large percentage of whom are known to experience similar
impairment in cognitive domains such as attention, as a result of their condition
(Doornhein & De Haan, 1998). It is within this setting that the current study was
conducted and as such, adds to a small yet growing pool of knowledge
demonstrating the efficacy of cognitive rehabilitation for attention deficit in stroke
patients.
The primary aim of the current study was to investigate the efficacy of a
commercially available attention remediation programme, the APT programme,
on attention deficit in the initial weeks after stroke. A further aim was to
determine if improved attention impacted on the patient‟s quality of life at this
early stage of recovery and a wider endeavour was to investigate what
characteristics might influence the ability to benefit from the APT programme.
Main Findings
This study demonstrated that the APT programme led to significant
improvement on the primary outcome, the Full Scale Attention Quotient (FSAQ)
of the IVA-CPT, as well as the Auditory Attention Quotient (AAQ) and the Full
155
Scale Response Quotient (FSRQ) of the IVA-CPT. On the secondary outcome,
the Mental Component Score of the SF-36, there was no significant improvement
as a result of the APT programme.
However, on the FSAQ, it was found that the APT group had significantly
lower scores on this measure than the standard care group at baseline. This means
that the attribution for the cause of the improvement that occurred on this measure
is unclear and cannot be solely attributed to the intervention. This was the only
attention measure in this study where there were differences between the groups at
baseline. At post-intervention both groups obtained similar scores suggesting a
ceiling effect for improvement on this measure.
On the IVA-CPT, AAQ, the APT group improved significantly but the
standard care group did not. This measure provides a measure of sustained and
selective attention in the auditory modality.
The APT intervention also led to significant improvements in participant‟s
performance on the FSRQ (impulsivity) which is a composite of prudence,
consistency and stamina. As the improvements in prudence scores were similar in
the APT and standard care groups it appears then that the intervention improved
consistency and stamina in particular. This suggests that the APT group was more
consistent in the ability to stay on task and more able to sustain effort compared to
the standard care group.
Not only were statistically significant improvements observed in attention
as a result of the APT intervention, there were also clinically significant
improvements as shown by the movement of participants‟ performances across
qualitative categories. Movement across qualitative ranges provides valuable
clinical information and to certain parties (i.e. patients, rehabilitation specialists,
156
behavioural researchers), is perhaps more meaningful than the statistical findings.
Overall, on the IVA-CPT, FSAQ, AAQ, and FSRQ, there was a considerable shift
by people in the APT group out of the low qualitative ranges, resulting in an
increase in the number of participants reaching higher qualitative ranges. The
pattern of movement across qualitative ranges generally reflected the statistically
significant improvements from baseline to post-intervention obtained by the APT
group. In contrast, there was considerably less movement by people in the
standard care group out of the very impaired range and as a consequence
considerably fewer standard care participants reached the average range. For both
groups movement into the above average and superior ranges was limited to a
small number of participants.
In summary, this study found that performance for the APT group improved
on three attention measures, the FSAQ, the AAQ and the FSRQ at the posttreatment stage of APT. However, of those three measures the FSAQ was
confounded by the differences on that measure at baseline. A clinical profile of
the changes the participants made from pre to post intervention closely resembled
the statistical findings.
Similarities with other studies
The outcomes of this study have some similarities to those reported in the
literature. First, comparisons will be made with other studies that evaluated APT
with a stroke sample. This included three studies; Boman et al. (2004), Sinotte
and Coelho (2007), and Sohlberg and Mateer (1987). In their study, Boman et al.
(2004) found improvements in attention, specifically in complex sustained and
selective attention tasks after APT although no change was found on an auditory
attention task in that study. Sohlberg and Mateer (1987) and Sinotte and Coelho
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(2007) also found that the two stroke participants in their studies, improved on
measures of attention after APT.
Other studies evaluating APT did not include stroke patients but did utilise
the same outcome measures and as such are also somewhat comparable. For
example, a continuous performance task was used as an outcome measure in four
previous studies investigating the efficacy of APT (Butler & Copeland, 2002;
Kurtz et al., 2001; Lopez-Luengo & Vaaquez, 2003; Sohlberg et al., 2000). The
results of the IVA-CPT, obtained in the current study are similar with the findings
in three of those previous studies (Butler & Copeland, 2002; Kurtz et al., 2001;
Sohlberg et al., 2000) where scores also improved on a continuous performance
task, the Conners Continuous Performance Test (CPT), (Conners, 1992), (a
measure of sustained attention in the auditory modality), after APT had been
administered.
On another measure, the Bells Cancellation Test the outcomes of the current
study were similar to the findings in the Lopez-Luengo and Vaaquez (2003)
study, in that the participants in both studies did not demonstrate any
improvement on that measure. In the Lopez-Luengo and Vaaquez (2003) study,
both the participants in the experimental condition and the control group did not
improve. However, in the context of their performance at baseline this is perhaps
not a surprising outcome. That is, the baseline performances for both those
groups as with the APT group in the current study fell within the normal range,
thus limiting the scope for improvement. That is, those participants without an
attention deficit are less likely to benefit from APT due to ceiling effects.
The current study also failed to find a difference in the scores on either trial
of the Trail Making Test as a consequence of APT. This is another finding
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consistent with Lopez-Luengo and Vazquez, (2003) who also did not find a
change on this measure as a result of the APT intervention.
Differences from previous studies
It is perhaps surprising that there were a number of attention measures used
in the current study that did not show an improvement after APT as they did in
some of the previous studies. Some of this difference can be explained by the
variation in the methodologies between this and other studies. For example, there
has been wide diversity in the samples used in these studies including patients
with stroke, TBI, cancer, as well as patients with neuropsychiatric disorders.
Furthermore, participants have all been at various stages post-onset and
assessments have occurred at different times. The measures used in the studies
have also been very diverse. These are all common problems that threaten the
validity of comparing across studies and thus highlight the need for standardised
practises in methodology.
In the current study, the PASAT is one of the measures on which the
participants‟ score did not improve after treatment in the current study. This
result is in contrast to previous studies which utilised the PASAT when evaluating
APT. Indeed, the authors of APT, Sohlberg and Mateer, (1987) base their claim
for the general effectiveness of this programme on the results of their study when
all four participants improved on the PASAT following completion of the
programme. The other outcome measure used in that study was the Spatial
Relations subtest (SR) of the Woodcock-Johnson Psycho-educational Battery
(Woodcock, 1977) which did not result in a significant change. From these
results, the authors claimed that change occurred on the PASAT scores because it
drew on attention skills which had improved as a result of the intervention
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whereas the SR task was facilitated by other cognitive skills which were not
subject to training and therefore did not improve. They therefore concluded that
APT improved the functioning of specific cognitive processes underlying
attention, but did not improve general cognitive functioning.
Improvement on the PASAT was also found in three other studies (Palmese
& Raskin, 2000; Park et al., 1999; Sohlberg et al., 2000) although in one study
(Park et al, 1999), the control group also improved on the PASAT leading to some
ambiguity in the findings. In that study, only the experimental group showed
improvement on the other neuropsychological measure, Consonant Trigrams. The
authors speculated that this improvement may have resulted as a consequence of
the practice of skills performed throughout attention process training that were
similar to those skills required to successfully complete Consonant Trigrams.
That speculation fits with a learning specific skills approach for cognitive
rehabilitation purported by Kolers and Roediger (1984), Morris, Bransford, and
Franks (1977) and Roediger, Weldon and Challis (1989) rather than the improved
cognitive function hypothesis as postulated by Sohlberg and Mateer (1987). The
specific skills approach asserts that improvement is the consequence of learning a
skill rather than an improvement in functioning of an underlying cognitive process
and therefore will not tend to generalise (Park et al., 1999).
Another measure for which the treatment group in this study did not show
an improvement after the intervention was the Bells Cancellation Test. This is in
contrast to the findings of the Kurtz et al. (2001) study which found that two
participants did significantly improve their performance on a letter cancellation
task by 22% and an impressive 66% respectively, and the second participant‟s
performance also improved on a symbol cancellation task by 51%. Although the
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third participant‟s performance did not improve significantly on this type of task,
there was nevertheless a reduction in the time it took to complete the task at the
second measure. The fact that no significant improvement was made on the
cancellation tasks by any of the three control participants led the researchers in
that study to assert that sustained visual attention improved as a result of the
cognitive rehabilitation procedures adopted in that study which was primarily
APT; although a prospective training model (memory for upcoming events) was
also included.
Health Related Quality of Life results
As well as investigating changes on neuropsychological measures of
attention it was important to determine if APT actually improved the subjective
experience of the participant‟s daily life. The inclusion of such a measure was in
response to the often raised criticism of cognitive rehabilitation that while
patients‟ test scores may alter as a result of intervention, it does not address how
those changes may impact on real life, family, social and vocational settings.
Hence, the Mental Component Score of the SF-36 was selected for inclusion of
study outcomes. However, on this measure no significant changes were found as
a result of time or treatment. Previous studies of APT have not included a health
related quality of life measure although two studies of neglect interventions
(Antonucci et al., 1995; Wiart et al., 1997) did, with the improvements that
resulted on the neglect measures in both studies, generalising to everyday life.
However, the lack of significant change in this study was somewhat unexpected in
light of increasing recognition in the literature that cognitive deficits and even
mild cognitive impairment impact on functional and psychiatric outcomes of
neurological disorders (Mitchell et al., 2010).
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One explanation for this outcome may be because many of the participants
were still in hospital and therefore not able to respond accurately to those
questions that evaluated performance in their “normal” setting, i.e. home or work,
such as in question 6; “During the past 4 weeks, to what extent has your physical
health or emotional problems interfered with your normal social activities with
family, friends, neighbours, or groups?”. Another reason may have been because
the time between pre and post-measures (approximately five weeks) was not long
enough for change to occur or were so subtle as to fall outside the sensitivity of
the SF-36 such as in question 2; “Compared to one year ago, how would you rate
your health in general now?” Unlike other quality of life measures such as the
Cognitive Failures Questionnaire which assesses cognitive problems in daily life
(Broadbent et al., 1982), the SF-36 does not factor so well on the cognitive
domain of attention, the cognitive function that is targeted by the APT
programme. Therefore it is possible that any change in attention abilities that may
have occurred as a result of the intervention in this study is less likely to have
been detected by the SF-36, particularly given that some participants were still
hospitalised.
In summary, quality of life did not appear to alter as a result of the APT
intervention however it is possible that a more cognitively demanding quality of
life measure such as the Cognitive Failures Questionnaire (Broadbent et al., 1982)
may have been more able to discern a difference given that it was a cognitive
intervention that was being evaluated. The CFQ was administered at baseline and
again at six months post-intervention for the START analysis, however no
measure was obtained at 5 weeks.
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Changes as an effect of time
As well as improvements in some aspects of attention as a result of APT,
there were also improvements that occurred in both the APT and standard care
groups. Specifically, significant improvements were found on the IVA-CPT,
Visual Attention Quotient, both trials of the TMT, the faster trial of the PASAT,
and the Bells (Left) Cancellation Test as a function of time.
This improvement on neuropsychological measures as a function of time
since stroke has been seen in a number of other studies where the improvement
was not attributable to the treatment. For example, in the Park et al. (1999) study,
the control group improved significantly on the PASAT and in the Lopez-Luengo
and Vaaquez (2003) study, the control group improved significantly on a dichotic
listening task. Trends towards improvement, although not reaching significance,
have also been noted as in the Sohlberg et al. (2000) study, when after controlling
for practise effects, times for both trials of the TMT were shorter for the control
group when measured at three subsequent stages throughout the study. Similarly,
in the Lopez-Luengo and Vazquez (2003) study, the control group improved their
performances on both trials of the TMT. These findings are consistent with the
literature explaining the phenomenon of spontaneous recovery of cognitive deficit
(Christensen et al., 2008; Williams, Potter, & Ryland, 2010; Wilson, 2010)
specifically for attention deficit, within the first three months post-stroke
(Hochstenbach, Den Otter, & Mulder, 2003; Wade et al., 1988). In contrast, two
previous studies evaluating APT, did not find any improvement of cognitive
functioning by the control groups as measured by neuropsychological testing
(Butler & Copeland, 2002; Kurtz et al., 2001).
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Spontaneous recovery is a consequence of time and refers to the brain‟s
ability to repair itself, or more accurately, it is the neuronal re-organisation that
takes place the instant the injury occurs and is influenced by pre-injury and postinjury factors. While the variability of this recovery is substantial generally
recovery reaches a plateau within six months after brain damage (MunozCespedes, Rios-Lago, Paul & Maestu, 2005; Richardson & Richardson, 2002;
Rohling et al., 2009) including stroke (Cramer, 2008; Kreisel, Bazner ,&
Hennerici, 2006; Witte, 1998). As spontaneous recovery can occur with or
without rehabilitation, the presence of a control group that does not receive any
intervention is one method of assessing this phenomenon. The effects of
spontaneous recovery may also be seen in the current study where significant
positive correlations between “Time since stroke” and attention were evident for
10 of the 13 baseline attention measures. That is, scores on those measures of
attention improved the longer the interval since the stroke first occurred.
To conclude this aspect of the discussion it was found that improvement on
a number of measures occurred as a function of time, a finding that is consistent
with previous similar studies. Spontaneous recovery is largely responsible for this
recovery although extraneous variables may contribute to the improvement.
Appropriateness of measures
The lack of consistency on some measures between the current study and
previous studies gave rise to the notion that perhaps those measures that have
been used across studies may not be entirely appropriate for use with a stroke
population and therefore have led to inconsistencies in outcomes. The lack of a
positive outcome on the PASAT in this study warrants some scrutiny for the
suitability of this measure. The number of participants who were unable or
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unwilling to complete the PASAT was considerable and may have contributed to
the insignificant finding at post-intervention. Some participants after being
provided with instructions and presented with the PASAT practice list, considered
the task too difficult and declined to continue, while others aborted the task soon
after commencement. One explanation behind that resistance could be that the
age of the sample, compared to previous studies, was much older and therefore
not as able to cope with the demands of this task. This raises the question as to
the suitability of the PASAT in studies of stroke patients, a population which is
largely made up of elderly participants. Indeed, the PASAT is a highly
demanding task of auditory working memory and has frequently been reported as
being too challenging and stressful for some populations including the elderly, for
whom working memory is generally adversely affected (Holdwick & Wingenfeld,
1999: Raz, 2000; West & Bowry, 2005), regardless of their cognitive status
(Tombaugh, 2006).
Another reason for low participation rates could be that a number of the
participants were experiencing heightened fatigue. Indeed, it has been found that
patients who experience attention problems often experience difficulty with
fatigue and/or maintaining concentration over an extended period of time
(Sohlberg & Mateer, 2001). Difficulty undertaking the PASAT has been
previously recorded. In their study determining cognitive dysfunction in patients
with first-ever brain infarct Cohen, Salloway, & Sweet (2008) found that fatigue
impacted on the ability to undertake the PASAT. Furthermore, the high demands
of the PASAT can lead to anxiety and frustration and deter patients from further
engagement in this task (Tombaugh, 2006).
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In another study, patients performed significantly lower than the control
group on the Modified PASAT and the authors pointed out that those structures
requiring activation to perform this task (i.e., the prefrontal cortex and posterior
parietal cortex) had been damaged by the stroke (Jaillard, Naegele, TrabuccoMiguel, LeBas, & Hommel, 2009). So it may be that in this study, age, fatigue,
location and severity of stroke were all factors contributing to some unwillingness
to complete the task which ultimately resulted in low participation rates for this
measure. However, despite its drawbacks the PASAT is a highly reliable measure
and very sensitive to subtle attention deficits which is why it was used in this
study. It is also the most used primary outcome measure in previous studies of
APT.
There has also been some concern amongst researchers regarding the
suitability of the TMT as a neuropsychological measure for stroke patients. A
major criticism of the use of this measure in a stroke population is that
performance has frequently been compromised due to non cognitive factors such
as motor dysfunction of the dominant hand or hemianopia (Lezak, 1995;
Waldstein, et al., 2003). The diminished ability of stroke patients on this task was
vividly demonstrated in a study of patients with sub-cortical ischemic vascular
lesions who demonstrated pronounced impairment of speed on both trials of the
TMT (Peters et al., 2005) compared to matched controls. In fact, the
inappropriateness of the TMT in patients with physical restrictions has long been
established and has subsequently led to the development of the oral paradigm of
the TMT which was clinically validated on a stroke population (Ricker, Axelrod,
& Houtler, 1996). It is perhaps because of this limitation of the TMT that no
differences were found in this study. Participants with subtle physical limitations
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were not identified and therefore may have influenced outcomes on this measure.
Given the potential of the TMT to affect the performance of participants with
physical limitations, it may be more appropriate for future studies with stroke
survivors to utilise the oral TMT.
Another measure that may have influenced performance level with this
sample is the Victoria Stroop Test. On this task the participant was required to
distinguish between the colours blue and green in order to make a correct
response. However, it has been found that some older people suffer from
impaired visual acuity due to a range of problems and may include difficulty in
discriminating the blue-green dyad. This condition is due to the yellowing caused
by the presence of cataracts (Pachana, Thompson, Marcopulos, & Yoash-Gantz,
2004). In order to counterbalance this problem Pachana et al. (2004) developed
an alternate form of the Stroop called the California Older Adults Stroop Test
(COAST). This modified version uses larger type face, fewer items and the
colours red, yellow and green, which are more easily distinguishable. Although,
in hindsight utilisation of the COAST may have been more appropriate given that
the average age of the sample was 69.03 years, when designing the study, it was
considered more appropriate to use the Victoria Stroop Test which is less age
restrictive and because of the potential for a younger sample. That is, the primary
site for recruitment was south Auckland which has a large Maori and Pacific
Island population, two demographic groups that suffer stroke at a much younger
age than their European counterparts (Fink, 2006). Nonetheless, the COAST is an
appropriate measure of selective attention in further studies of older people.
The SF-36 is another measure used in this study that has its proponents
and critics (Hagell, Reimer, & Nyberg, 2009; Jenkinson et al., 2002; Ware, 2000).
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Some research has evaluated the SF-36 with elderly patients (Hayes, Morris,
Wolfe, & Myfawny, 1995; Loge, 1998) and more specifically with elderly stroke
patients (Hobart, Williams, Moran, & Thompson, 2002), including those in New
Zealand (Bonita et al., 1997; Hackett et al., 2000) with mixed conclusions. A
study conducted in Sweden with 188 acute stroke survivors with a mean age of 74
years found the Swedish version of the SF-36 to be an effective measure of
HRQoL when administered two to three weeks after discharge from hospital
(Almborg & Berg, 2009). In their study Hagen, Bugge, and Alexander (2003)
also found the SF-36 to be an adequate and reliable measure with their stroke
sample revealing particular sensitivity to change between one and three months
post-stroke although poor sensitivity between three and six months.
Critics of the SF-36 include Hackett et al. (2000) who suggest that the SF36 “may not be sensitive or specific enough to detect the psychological domains
of mental health that are relevant to patients with stroke” (p.446), although their
sample group consisted of long-term rather than short-term survivors of stroke.
Anderson, Laubscher, and Burns (1996) also found that the Australian version of
the SF-36 did not characterise social functioning very well and suggested that it
be supplemented with other measures in order to gain a comprehensive
assessment of stroke outcome. Furthermore, a number of researchers have found
floor and ceiling effects for the SF-36 (de Haan, 2002; Dorman, Dennis, &
Sandercock, 1999; Hobart et al., 2002; O‟Mahoney, Rodgers, Thomson, Dobson,
& James, 1998) and therefore advise caution on this measure, although others
have not (Anderson et al., 1996). Fortunately, no such effects occurred in this
study. Finally, the inadequacy of completion rates of the SF-36 has been shown
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in the elderly who were contacted by post (O‟Mahoney et al., 1998; Parker, Peet,
Jagger, Farhan, & Castleden, 1998).
However, there are many benefits for the use of the SF-36 that led to its
inclusion in the current study. It has been consistently shown to have good
validity, reliability and sensitivity across various populations (Fukuhara, Bito,
Green, Hsiao, & Kurokawa 1998; Gladman, 1998; Sanson-Fisher & Perkins,
1998), including Maori, Pacific and New Zealand European ethnic groups (Scott,
Sarfati, Tobias, & Haslett, 2000; Scott, Tobias, Sarfati, & Haslett, 1999).
Almborg and Berg, (2009) found the SF-36 to be a valid measure of health-related
quality of life in a study of 188 post-stroke patients, and Mead et al. (2011) found
it to be a valid measure of post-stroke fatigue.
Conversely, the IVA-CPT was shown to be an entirely appropriate
measure with this stroke sample. Of all the measures used in this study the IVACPT was the most consistent in detecting change. One reason for these positive
findings may be due to the highly sensitive properties of the IVA-CPT and its
ability to detect slight change, compared to other measures of attention. For
example, the IVA-CPT is frequently used when evaluating children with attention
deficit because it has been found to be the most sensitive measure for detecting
the subtle impact of treatment regimens with this population (Harding, Judah, &
Grant, 2003; Sandford, Fine ,& Goldman, 1995). Furthermore, it is distinct from
other attention measures in that it combines scores from both visual and auditory
modalities and therefore is able to detect change in more than one modality. The
versatility and sensitivity of this measure renders it a highly appropriate measure
of attention deficit in studies of stroke patients.
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Although the measures used in this study are generally well supported for
use in a stroke population the previous paragraphs have identified possible
problems of some of the measures as well as the strengths of other measures.
Further research of post-stroke cognitive functioning will increase confidence in
which measures are most appropriate and scientifically valid. The ultimate goal is
an understanding by researchers of standard measures for use with specific study
designs and specific stroke sub-groups.
Factors that may have influenced outcomes
The subjective experience of APT is also of interest to rehabilitative
researchers, therapists and perhaps most of all, to the survivors of stroke who
present with attention deficit. Observations and experiences from both the
researchers and the participants who received APT will now be discussed.
The majority of participants in this study did not complete the full 30 hours
of intervention and the reasons for this trend were varied although most
commonly, participants did not offer a reason for their decision to cease
participation in the intervention. However, the most frequent reason that was
given, was that participants experienced heightened fatigue and they found that
participation in the study was too taxing and/or challenging. Other participants,
particularly those engaged in outpatient services found that it became too difficult
to accommodate the study because so much of their time was being taken up with
other appointments. Other reasons for reduced participation in the study included,
participants returning to work, participants going on holiday, or general loss of
motivation to take part in the study. One patient completed all APT tasks in less
than the 30 hour maximum time period and another participant moved away from
the area. Another patient died soon after the study began. In essence, the course
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of some of the participants‟ lives after the stroke became somewhat unpredictable,
less routine and more demanding and the consequence was that compliance to the
study was affected.
In light of the evidence that intervention dose (i.e., amount of training)
impacts on outcomes (Sohlberg & Mateer, 2001; Velligan, Kern, & Gold, 2006) it
was speculated that those participants who completed more APT may have
produced better post-treatment attention scores. There was considerable range in
the number of APT hours completed by the participants, however, despite
expectations there were no statistically significant relationships between the
number of APT hours completed and performance on the post-intervention
attention measures. (See Appendix F for the correlations between postintervention measures of attention and total hours of treatment). Comparison of
these relationships with other studies of APT is not possible as previous data is
not available.
Second, what was also noted in this study was that the participants
progressed considerably further on auditory tasks than they did on visual tasks.
This pattern was possibly a consequence of the order in which the tasks were
administered. All participants were administered the APT in a pre-determined
order. Of the first nine tasks administered, seven were in the auditory modality.
(See Table 6, p 109, in the Methods Section). Only two participants in the APT
group progressed beyond task nine and therefore most participants did not engage
in tasks presented in the visual modality. This order of administration gave rise to
speculation that the significant result obtained on the Auditory Attention Quotient
of the IVA-CPT may be related to the greater amount of training received in the
auditory modality of the APT programme. However, as previously mentioned,
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analyses did not reveal any such significant association between how far the
participants reached on either auditory or visual tasks with post-treatment
attention measures.
Factors that may have influenced how the participants engaged in APT
There were other behaviours exhibited by the participants that may have
influenced how they engaged in the intervention. For example, it was observed
that tolerance levels of the participants for the APT programme varied
considerably and was believed to have been largely influenced by levels of
fatigue. The range in the number of total hours of APT achieved by the
participants was extremely varied ranging from three quarters of an hour to the
maximum of 30 hours (See Table 7, p 119). Of those participants who ceased
involvement in the study before completion of the scheduled 30 hours, heightened
fatigue was the most quoted reason for their withdrawal. It is widely
acknowledged that fatigue compromises cognitive abilities (Barker-Collo et al.,
2007; Englander, Bushnik, Oggins, & Katznelson, 2010; Fry, Greenop, & Schutte,
2010; Gehring et al., 2009; Roth, Geisser, Theisen-Goodvich, & Dixon, 2005). In
their study of patients with attention problems, Sohlberg and Mateer (2001),
found that fatigue was a recurring factor amongst those patients who completed
fewer hours of APT. Boman et al. (2004) were aware of this problem also and
acted to minimise the effects of fatigue in their evaluation of APT with
neurologically compromised patients, by ensuring that the intervention was
administered in the morning. Unfortunately, in the present study scheduling of
the intervention for the hospital-based participants was typically out of the control
of the researchers and therefore occurred whenever it was convenient for
participants and hospital staff. Usually standard care took place during the
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morning hours leaving mid to late afternoon to conduct the APT intervention. By
that time, participants were already experiencing heightened fatigue and were less
tolerant of the APT intervention. Whenever it was possible participants who had
been discharged home were scheduled to receive the APT in the morning and it
appeared that those participants performed better, however, this is the observation
of the researcher only as formal data for these variables was not obtained. This
observation is however consistent with the literature for traumatic brain injury that
cognitive fatigue increases throughout the day (Brain Injury Association of
Canada; Claros-Salinas et al., 2010). Therefore it is possible that the morning
hours appear to be the ideal time to administer APT for participants to gain
optimal benefit from the programme.
Another behaviour that appeared to impact on participants‟ engagement in
the intervention, was their level of motivation. Although again not formally
assessed, it became evident to the researcher throughout the course of the
treatment that there was considerable variability in the willingness of the
participants to engage in the intervention. Despite having consented to
participating in the study some participants were reluctant to actually engage in
the intervention. In contrast other participants were compliant and willing
throughout. The researchers felt that this factor may have influenced performance
on the APT.
Motivation has been identified as having an influence on the performance of
individuals who participate in research studies and is linked to the reasons why
they agree to being involved in research. That is, intrinsic factors such as „a sense
of the importance of scientifically controlled studies‟ or „to gain more knowledge
about their own condition‟ are usually more influential (Bell et al., 2008), than
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extrinsic factors such as monetary rewards (Patel, Doku, & Tennakoon, 2003). It
is possible that generally, those participants who considered the intervention to be
of value to their own recovery maintained a higher level of enthusiasm and
engagement throughout the intervention process compared to those whose reason
for participating in the study was prompted by a “social conscience”. The least
motivated as demonstrated by their decreased willingness to engage in the
intervention, appeared to be those individuals whose participation in the study was
primarily due to persuasion by family members. Some patients in this latter group
also expressed feelings of depression and not only lacked motivation to engage in
this study but demonstrated similar ambivalence to any form of rehabilitation.
Providing feedback after each task appeared integral to the success of the
intervention. When the feedback was positive such as when the participant
committed fewer errors or false alarms, increased motivation was apparent as
noted by behavioural responses. When the participant‟s performance was not
improving or even sometimes if it was regressing, care was taken to express the
feedback in a way designed to avoid de-motivation.
The current study recruited participants who were in the very early stages of
recovery from their stroke and although no formal measures of depression or
anxiety were implemented, there were indications that some participants were
suffering from the emotional impact of stroke. The presence of heightened
emotion is consistent with the literature identifying depression as a relatively
common stroke outcome (Barker-Collo, 2007; Hackett et al., 2005; Paolucci,
2008). This generated some concern as to whether the participant‟s emotional
status was impacting on their performance on the APT. Certainly, this concern
was not without foundation as there exists a significant amount of literature
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linking Post Stroke Depression (PSD) with cognitive impairment (Murata et al.,
2000; Narushima et al., 2003; Robinson et al., 1986; Saxena, 2006; Talelli et al.,
2004; Yoo et al., 2009). Given the frequency of PSD and its possible
confounding effects, it may have been prudent for a specific measure of
depression to have been included in this study. In their study, Park et al. (1999)
used the Beck Depression Inventory (BDI), to assess the impact of the APT
programme on mood, although on that occasion there was no significant change
detected on the BDI scores. However, there are other depression scales that may
be more suited to a stroke in-patient population including the Poststroke
Depression Rating Scale, the Hospital Anxiety and Depression Scale, the
Hamilton Rating Scale for Depression and the Geriatric Depression Scale all of
which have been validated with this population (Aben et al, 2002; Tilanus &
Timmerman, 2005).
The preceding paragraphs provide some observations made by the study
researchers, of the behavioural factors that may have influenced how the
participants engaged with the APT programme. In summing up, this study
demonstrated that administration protocols as well as physical, psychological and
emotional functioning of the stroke patient in the early stages of recovery can
affect the extent to which the patient engages in APT.
Which patients might benefit most from APT?
It was considered important to collect data on the characteristics of those
individuals who might benefit more from APT. In order to do this, relationships
between participants‟ demographics and baseline performances on
neuropsychological tests and progression on APT were investigated. Five
positive associations were identified. First, those participants who obtained a
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better MMSE score had a positive association with the number of hours of APT
that were completed as did those participants who had a better performance on the
baseline Auditory Prudence score. One possibility for this outcome is that those
participants with higher MMSE and Auditory Prudence scores found the APT
tasks easier and therefore were more likely to progress through the programme.
However, although participants with better cognitive functioning might do better
on cognitive rehabilitation tasks, they are more susceptible to the ceiling effects of
rehabilitation tasks but are also less likely to require rehabilitation.
Three further significant relationships emerged from this analysis and
perhaps not surprisingly, both relationships were specific to their respective
modalities. That is, a better performance on the Bells Right task (a visual task)
was associated with achieving a higher visual task on APT and a better
performance on both trials of the PASAT (an auditory task), was associated with
achieving a higher auditory task on APT. Although these findings are of interest,
the presence of only four significant relationships is not sufficient data to argue
that neuropsychological performance, at least in this study, influenced
performance on APT. It does however provide consideration for modalityspecific training where the participant is initially assessed for impairment in either
or both auditory and visual modality and rehabilitation is provided accordingly.
Attention abilities of stroke survivors in the early stages of recovery.
The current study also provided an opportunity to investigate the attention
abilities of stroke survivors in the early stages of recovery. As part of the
inclusion criteria for the study all participants had been found to have an attention
deficit as determined by their score of one standard deviation or more below the
normative mean on any scale of the IVA-CPT, the Trail Making Test Part A or B,
176
either trial of the PASAT or if they missed more than 3 bells on the left or right of
the Bells Cancellation Test. A series of correlations showed that some baseline
attention scores were found to have significant positive relationships with “Time
since Stroke” and scores on the Barthel Index and the Mini Mental State Exam.
The association between „Time since Stroke” and an improved performance on
baseline attention measures has already been discussed in this chapter within the
context of spontaneous recovery. A significant correlation between the Barthel
Index and six attention measures was found which is somewhat surprising, given
that an often cited weakness of the Barthel Index is its failure to measure activities
that require cognitive abilities. According to Herndon (2006), patients can have
significant cognitive impairment and still obtain a perfect score on the Barthel
Index. However, in this study the Barthel Index was one of the factors of
randomisation and therefore properties of this measure would have been balanced
across the APT an SC groups.
The significant correlations that were found between the MMSE and six
baseline attention measures was not surprising given that it is a measure of
cognitive functioning and attention is one of the five areas of cognition that is
specifically tested by this instrument (Folstein et al., 1975). All participants had
to have obtained ≥20 on the MMSE for inclusion into the study.
Also of interest was the interplay of baseline attention measures with
neuropsychological measures of memory, language and executive functions. Of
all the neuropsychological measures, performance on the ROCF was associated
with more measures of attention than any other measure. The significant
correlations between the delay and recognition trials of the ROCF and attention
measures is consistent with the argument that attention is a precursor to other
177
cognitive functions such as memory (Cowan, 1995) and also corresponds with the
statement that a good performance on the short delay trial of the ROCF is reliant
on intact working memory (Lezak, 1995). Furthermore, most of the attention
measures that correlated significantly with the ROCF were in the same modality,
i.e. visual. However, an interesting finding was that the BNT, a measure of the
verbal modality, correlated significantly with six of ten attention measures that
were in the visual modality.
The variability of the performances of stroke patients as measured by
neuropsychological tasks is largely dependent on the many factors that affect the
presentation and experience of the disease and the stage at which the person is in
the recovery process. Factors that influence recovery rate are wide and varied and
can include; type of stroke, severity of stroke, site of the lesion, previous stroke,
neurological deficits, loss of consciousness, type and amount of therapy provided,
timing of therapy, the presence of neglect (especially in cancellation tasks),
awareness of the neglect (anosognosia), cognitive status, as well as demographic
characteristics such as age, gender and education (Barker-Collo & Feigin, 2006;
Brandt, 2007; Cumming, Plummer-D‟Amato, Linden, & Bernhardt, 2009;
Gialanella, Monguzzi, Santoro, & Rocchi, 2005; Kumar, 2003; Menon-Nair,
Korner-Bitensky, & Ogourtsova, 2007; Stone, Patel, Greenwood, & Halligan,
1992), although this is by no means an exhaustive list of variables that affect the
path of recovery.
The preceding paragraphs provide some insight into the attention and wider
neuropsychological abilities specific to the study sample. It would be useful if
future research built on this data so as to develop a knowledge base of the
178
attention profile of stroke patients sub-groups. This information would then be
useful data for comparing across studies.
Limitations
There were a number of limitations identified in this study, the main one
being the failure to ensure a balance for the primary outcome at baseline across
the two groups. This oversight makes it difficult to draw firm conclusions
regarding the efficacy of APT. It is uncertain whether or not the APT group
would have demonstrated as much improvement if their baseline measure was
equivalent to the SC group. Future studies should ensure that baseline measures
for the primary outcome are equivalent across the groups.
Another possible confounding variable in this study was the use of one
standard deviation on the primary outcome measure as the criteria to determine if
the intervention was effective. The authors of the IVA-CPT reported a test re-test
correlation for the composite quotient scores as ranging from .37 to .75 (Sandford
& Turner, 2009). These relatively weak coefficients make it difficult to reconcile
that an observed effect of just one standard deviation should be interpreted as not
likely to be due to random fluctuations. Future studies may consider increasing
the criteria for an observed effect to more than one standard deviation.
Another limitation of this study was the relatively narrow inclusion criteria
of the sample. Only patients who had experienced first-ever strokes were
included into the study thereby limiting the findings to that particular group of
stroke survivors. Furthermore, restricting recruitment to patients who had
suffered their stroke within the previous 30 days means that the findings are not
able to be generalised to non-acute stroke survivors. Of course, in contrast, the
advantage of the rather strict criteria is that it provided some control for the wide
179
variability in stroke patients meaning that the findings can be regarded as
representative of this particular group of stroke patients.
This study examined the movement across categories and as such provided
useful information in terms of a more clinical interpretation of the findings,
however, this approach does have some limitations which will now be discussed.
Using this approach, there is the possibility that a participant‟s true change may
not be evident. For example, a participant may make minimal improvement from
baseline to post however if at the baseline stage that participant is sitting at the
high end of a category the minimal improvement may be enough to re-classify the
participant into the low end of the next category. In another scenario, a
participant may make a significant improvement from baseline to post-treatment
yet not necessarily be re-classified into a higher category. This situation is more
likely to occur if at the baseline measure the participant is sitting at the low end of
the category. This condition was most clearly depicted in this study where the
„average range‟ category, based on the normal probability curve, included those
scores that fell between one standard deviation below the mean and one standard
deviation above the mean, thereby covering a range of two standard deviations.
This created a situation where a participant‟s performance from baseline to posttreatment may have been statistically significant however no change of category
would necessarily have occurred.
Another method of measuring the effectiveness of an intervention is to
calculate the effect size which, as the name implies, is a statistic that conveys the
strength of a treatment effect. Effect size is a useful adjunct to inferential
statistics by providing substantive evidence that further informs decision making
around meaningful treatment plans for clients. The z-scores of a standard normal
180
distribution as utilised in this study are an example of an effect size (Faraone,
2008). Thus comparing z-scores from pre to post-treatment in this study would
have also provided a clinical interpretation of the effectiveness of APT. Effect
sizes can be classified as portions of a z-score with “small effect size” being (0.2
to 0.5), “medium effect size” (0.5 to 0.8) or “large effect size” (0.8 and higher;
Coe, 2002).
The Reliability Change Index (RCI) provides another method for calculating
clinical significance. The RCI is the difference between a participant‟s pre-test
and post-test scores divided by the standard error of the difference (Jacobson &
Truax, 1991). Cut off scores are established to determine any clinical change that
may occur.
Thus, although this study examined the changes in categories to determine
a clinically significant change in performance, it can be seen that this method of
analysis is not without its problems. Future studies may consider utilising an
alternative method thereby avoiding the problems associated with the categorychange method.
Another limitation of the study may have been that the lack of evaluation for
depression or anxiety. Given that both of these states have the potential to impact
on cognitive performance, future studies should control for this possibility. The
Beck Depression Inventory-II and the Hamilton Rating Scale for Depression are
commonly used for screening depression in stroke populations however they were
not developed specifically with a stroke population in mind and as such overlook
some of the complex neurological problems involved in this disease. In response
to this problem, Gainotti et al. (1997) developed the Post-Stroke Depression
Rating Scale an instrument that is specifically designed to investigate affective
181
disorders of stroke patients who suffer various degrees of severity of depression.
As such this would be an appropriate tool to use in future studies when screening
for depression.
The APT did not impact on a health related quality of life measure at this
early stage however it may have been more appropriate to have conducted a
follow-up assessment of this domain at a slightly later stage when participants
were back in their usual environment and some of the questions that make up the
SF-36 would have been more relevant. Alternatively, the CFQ, which was
administered at baseline and again at 6 months for the START study, may have
been more useful at the 5 week post-stroke point compared to the SF-36, given
that the former is a measure more reflective of underlying neuropsychological
impairment.
Implications of this study
There is now general consensus within the practise of neurological
rehabilitation that cognitive rehabilitation is necessary to meet the needs of people
who suffer brain injury. Historically rehabilitation models were developed with
the primary purpose of addressing physical impairment and there still remains a
lack of empirically validated interventions routinely available to clinicians, for the
numerous cognitive impairments that affect this population. While the
understanding of non-spatial attention is grounded in theoretical models that have
developed and evolved over many decades, there are few theoretically-based
models of this phenomenon with a clinical application. Sohlberg and Mateer‟s
contribution to this area of cognitive rehabilitation, with the development of APT
has been an important and significant step in addressing this gap and the current
182
research has further sought to improve this situation by providing a well-designed
study for the evaluation of APT.
However, in many settings the rehabilitation programme continues to
remain wholly focussed on the physical consequences of stroke despite
considerable support for a multi-disciplinarian approach such as the stance taken
by the American Stroke Association (Schwamm et al., 2005). The inclusion of
cognitive rehabilitation into rehabilitative programmes will place demands on
already stretched resources so it is vital that studies such as the current one
continue to provide empirical evidence for the rationale and justification of
cognitive rehabilitation if it is to become a respected and integral component of
post-stroke rehabilitation.
While the overall findings of this study add to evidence-based practises, the
addition of qualitative findings is also encouraging to clinicians as it provides
further insight into the actual improvement of attention changes that occurred for
participants. Not only does this information increase the clinician‟s confidence in
the intervention but it also provides a framework for measuring change that can be
utilised in a rehabilitative setting.
Furthermore, this study provides support for the assertion that rehabilitation
for cognitive deficits should be initiated in the early stages of stroke recovery.
Hochstenbach et al. (1998) argue that advice and treatment for cognitive deficits
needs to be initiated earlier than three months post-stroke, however, early
neuropsychological assessment of stroke patients is not routinely carried out in
most hospitals (Hoffman, Schmitt, & Bromley, 2009).
183
Conclusions
APT appears to be a viable option for the remediation of attention deficit for
those people who are in the early stages of recovery from stroke. Significant
improvement was obtained on the primary outcome measure although
confounding factors rendered this particular result inconclusive. However,
improvements were also obtained on two other measures of attention after
administration of the APT. The impact of APT on quality of life measures at such
an early stage in the recovery process was not discernible. Factors that appeared
to influence the performance of participants when undertaking APT in this study
are fatigue and motivation levels so formal assessment of these issues are
recommended in future research in order to determine optimal application
parameters for this cognitive intervention.
This study in context with previous research evaluating APT contributes to a
steadily growing bank of data for the efficacy of APT since it was first developed
by Sohlberg and Mateer in 1997. This has been the first randomised controlled
trial of this intervention in a relatively large stroke sample and provides
encouraging data for its usefulness in neurologically impaired patients other than
those for whom the programme was first developed. The strength of this study
was in its design, in that it was a single blind randomised control trial. Inclusion
criteria ensured homogeneity of the sample group. The selection of outcome
measures resembling the training tasks did provide for an accurate gauge of any
changes that may have occurred for that specific skill although without other
measures in place generalising the findings to functional improvement was not
achievable.
184
Future Research
Hopefully, the results of this study provide incentive for further randomised
controlled trials for the efficacy of APT in acute stroke patients. The reasonably
strict inclusion criteria of the current study was intended in order to increase
confidence that any observed effects of the intervention, apply to this particular
group of stroke patients. However, more evaluation of APT with other sub groups
of stroke patients is also necessary. Patients with particular lesion sites, long term
stroke patients or survivors of recurrent stroke, are all examples of the different
stroke sub groups where the efficacy of APT needs further investigation in order
to determine its suitability for those particular groups. It is recommended that
psychological and physical problems often associated with stroke patients should
be considered and addressed in order to optimise the full benefits of this
intervention.
Future studies evaluating APT should also include follow-up measures
particularly to assess any real-life benefits to the individual. This could be
achieved by including measures of HRQoL, ADL‟s, functional measures, selfreporting questionnaires, and caregiver questionnaires.
This study briefly looked at other investigations of APT whose samples
included patients with schizophrenia ADHD, TBI and encephalitis. However,
there are many other neurological disorders such as Multiple Sclerosis,
Korsakoff‟s syndrome, Parkinson‟s disease, Huntington‟s disease and dementia,
plus other neurological conditions that may also result in attention deficit.
Research into the efficacy of APT as a viable rehabilitation intervention for those
conditions is needed.
185
There has also been little research conducted with children primarily
because the APT programme was designed for adults. However, Kerns Eso, and
Thompson (1999) and Semrud-Clikeman (1999) have conducted studies with
children using interventions based on APT with both studies producing results of
improved attention. However, given the maturing nature of a child‟s brain, APT
needs to be evaluated within narrow age bands in order to evaluate its efficacy
with each age band.
186
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Appendix A
Stroke Risk Factors
Non-Modifiable Risk Factors
This section will provide some background information on those risk factors
that are considered to be significant precursors of stroke.
Age.
Advancing age is strongly associated with an increase and prevalence of
stroke and is the principal non-modifiable risk factor for this disease (Falcone &
Chong, 2007; Petrea et al., 2009; Sacco et al., 1997). For each decade after the
age of 55, for both men and women, the risk of stroke more than doubles
(Cubrilo-Turek, 2004). Reasons for this increase include the increased exposure
to environmental risk factors and higher prevalence of risk factors associated with
age including atrial fibrillation, hypertension, diabetes, and coronary heart disease
(Wattigney, Mensah, & Croft, 2003).
Gender.
To date, research has produced contradictory findings for gender differences
in the epidemiology, outcomes and treatment of stroke. A recent worldwide
systematic review of the literature on gender differences in stroke epidemiology
concluded that although stroke is more common among men, women are more
severely ill. A number of studies have found that not only do men have higher
age-specific rates than women but compared to women men are also more likely
to have their first-ever stroke at a younger age (Appleros, Nydevik, & Viitanen,
2003: Petrea, et al., 2009; Roquer, Campello, & Gomis, 2003). Conversely, other
researchers conclude that due to a significant increase in the incidence of stroke
for women over the age of 84, women overall, experience more strokes (Niewada,
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Kobayashi, Sandercock, Kaminski, & Czlonkowska, 2005; Reeves et al., 2008).
This large increase in incidence in elderly women raises the possibility of
biological explanations such as the neuro-protective effect of estrogen. This
theory presents a challenging subject area for further research (Suzuki, Brown, &
Wise, 2009).
There is a growing body of research implicating gender as a confounding
factor for stroke sub-type, but again the findings are diverse and inconsistent. For
example, Appleros et al. (2003), Ayala et al. (2002), and Reeves et al. (2008),
provide evidence for higher incidence of subarachnoid haemorrhages in women
than men, although in another study, Bogousslavsky, Van Melle, and Regli
(1988), found a greater association with men than women for haemorrhagic stroke
in patients younger than 50 years old. In another study of residents of a European
city, the authors found the incidence rate for large-artery atherosclerosis, to be
twice as high for men than for women (Blacker & Brown 2002; Grau et al., 2001;
Kolominsky-Rabas, Weber, Gefeller, Neundoerfer, & Heuschmann, 2001)
although other studies have found age-related large-artery atherosclerosis to be
greater in post-menopausal women (Ahimastos, Formosa, Dart, & Kingwell,
2003; Goto, Baba, Ito, Maekawa, & Koshiji, 2007; Kingwell et al., 2001).
Possible explanations for these gender differences lie in genetic and hormonal
modulations, although a clearer understanding of these differences needs further
investigation.
A number of studies have consistently identified women as experiencing
poorer outcomes and greater dependency post stroke (Falcone & Chong, 2007:
Petrea, 2009; Reeves, et al., 2008; Roquer et al., 2003). The causes for these
disparities are explained by a number of factors. Overall women are older when
239
they have their stroke, they tend to have poorer pre-stroke functioning, more comorbidity, such as depression, are less likely to have social support and more
likely to be widowed or divorced (Reeves et al., 2008). Gender has also been
found to be a factor in other areas of stroke including, presentation (Falcone &
Chong, 2007), diagnosis (Smith, Lisabeth, Brown, & Morgenstern, 2005) and the
type of treatment used in acute stroke therapy (Smith, Murphy, Santos, Philips, &
Wilde, 2009). Indeed, while it appears gender is likely a marker for multiple
medical, genetic, and socio-economic factors concerning stroke, some researchers
caution that these differences are over-estimated and there is general consensus
that further studies are required to elucidate the situation (Falcone & Chong,
2007; Smith et al., 2009: Zhang et al., 2007).
Ethnicity.
Ethnicity is a complex and heterogenous concept incorporating a wide range
of characteristics such as biology, history, culture, language, and religion.
Fustinoni and Biller (2000) in their editorial on ethnicity as a variable in stroke
research, caution against assumptions and possible bias when classifying
ethnicity. For example, ethnicity is largely influenced by cultural attitudes; “what
is black to someone from the United States may be white to a Brazilian or a
Caribbean islander”. A number of studies have used self-classification in their
methodology (Bonita, Broad, & Beaglehole, 1997; Carter et al., 2006; Sacco et
al., 1998), however, the authors also point out flaws in this process such as
misinterpretation, confusion and self-reclassification. They give the example of
some respondents thinking that “South and Central American” referred to natives
of the south and central United States. They also discuss how the influence of
socio-economic and associated risk factors might be hidden within ethnic groups,
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with the example of affluent “blacks” from the US East Coast not necessarily
developing the same disease patterns as poor inhabitants from a comparable group
in the southern states. They suggest genetic research to determine common
ancestry may provide some clarity to the heterogeneity of ethnicity, which in itself
is a confounding variable. Fustinoni & Biller (2001) express concern that flawed
ethnic research might lead to an assumption that ethnic minorities are a social
health burden compared to “white” populations, thus adding fuel to racial
prejudices.
Harwood, McNaughton, McPherson, and Weatherall (2000), state that
despite the heterogeneity of ethnicity, it has nevertheless consistently been shown
to be a significant variable in increasing risk of stroke and has served particularly
well for providing a framework of understanding of difference in stroke outcomes
in the Pacific Rim region. They propose that research focusing on the inequities
of access and quality of stroke care for ethnic groups will be more rewarding than
research into genetics. Furthermore, they suggest that all viewpoints of ethnic
disparities in stroke incidence are worthy of further discussion and investigation
however in accordance with good research practice and to ensure the validity of
data particularly when comparing studies, researchers should clearly describe the
logic behind their "ethnic" groupings (Senior & Bhopal, 1994).
Evidence for ethnic disparities in stroke incidence, severity, and mortality
has continued to mount in recent years. Substantial evidence highlighting an
increased risk of stroke and increased mortality for ethnic minority groups has
emerged from a number of countries including the United States, the United
Kingdom and New Zealand. A number of studies have provided evidence that
ethnic minority groups tend to have their strokes at a younger age, (Bonita et al.,
241
1997; Bravata et al., 2005; Carter et al., 2006; Fink, 2006; Markus, et al., 2007;
Sacco et al., 1998; Wolf et al., 2002; Wolf & Kannel, 2007) even after
socioeconomic status had been factored out (Bravata et al., 2005; Howard et al.,
1995; Markus et al., 2007; Stewart et al., 1999). However, other authors have
found that socioeconomic status is the main contributing factor in the higher
incidence and mortality rate of stroke in ethnic minorities (Bravata et al., 2005;
Gillum & Mussolino, 2003; Maheswaran, Elliott, & Strachan, 1997). Howard et
al. (1995) argued however that although socioeconomic status is important in
stroke mortality risk, it is but one component of a complex picture that may
include a range of compounding factors. Other researchers also attribute a range
of risk burden factors such as, possible genetic susceptibility, hypertension,
hyperlipidaemia, diabetes, obesity, tobacco smoking and physical inactivity, as
determinants for the higher stroke incidence consistently found in ethnic
minorities (Carter et al., 2006; Feigin et al., 2006; Fink, 2006; Stewart et al., 1999;
White et al., 2005). Fink (2006), states that reduced stroke incidence observed
among European populations in New Zealand in the last 20 years can be credited
to improved primary and secondary prevention of cardiovascular disease, however
as he points out these are improvements that have not been achieved among Maori
and Pacific people in New Zealand. A similar observation is made by
Heuschmann, Grieve, Toschke, Rudd, and Wolfe (2008) in their study
investigating a 10-year ethnic trend in stroke incidence with the South London
Stroke Register, where they attribute the decrease in whites‟ incidence of stroke
compared to blacks, to changes in prior-to-stroke risk factors. Compared to
whites, blacks had made fewer gains in reducing rates of hypertension, diabetes,
smoking and atrial fibrillation.
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Epidemiological studies of migrating populations also consider the
management of risk factors as major determinants in stroke incidence for ethnic
groups. For example, Khaw (1996) points out that rates of strokes for Japanese
populations in the United States are closer to American white populations than
Japanese populations in Japan and suggests better medical care, changing severity
of disease and reduced case fatality are responsible for the lower rates in the
United States.
Modifiable Risk Factors
Hypertension.
Hypertension, also known as high blood pressure, is believed to be
responsible for about 60-70 % of all strokes world-wide (Cubrillo-Turek, 2004;
WHO, 2009). Over time, damage to the arteries caused by high blood pressure
impairs blood flow by the rupturing of the blood vessel or by causing plaque to
build up thus creating a clot which can then cause a stroke. Hypertension is
considered to be the most important modifiable factor in reducing the incidence of
stroke. (Aszalos, Barsi, Vitrai, & Nagy, 2002; Herekar & Hilal, 2008; Khan,
Rehman, Shah, &, Jielani, 2006; SHEP Cooperative Research Group, 1991;
Straus, Majumdar, & McAlister, 2002). In their statement for the Primary
prevention of Stroke, professionals from the Stroke Council of the American
Heart Association identified elevated systolic blood pressure with or without an
accompanying elevation in diastolic blood pressure, as increasing the risk of
stroke (Goldstein et al., 2001). Several other authors have implicated elevated
systolic blood pressure in increased risk of stroke (He & Whelton, 1999; Kannel
et al., 1981; Kurl et al., 2001). The treatment of hypertension has been
consistently demonstrated for lowering blood pressure yet despite this knowledge,
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a significant proportion of people remain undiagnosed or inadequately treated for
hypertension (Goldstein et al., 2001; Hypertension Detection and Follow-up
Program (HDFP), 1982).
Atherosclerosis.
Atherosclerosis refers to the thickening of the artery walls as a result of the
build up of plaque which is made up of fatty materials such as cholesterol, fat,
calcium and other substances found in the blood. When the arteries supplying the
brain are partially or totally narrowed, blood flow is obstructed resulting in a
stroke. Alternatively, pieces of the plaque itself or clot that forms on the plaque
can break off and block off smaller arteries downstream (Di Tuliio, Homma, &
Sacco, 2008; O‟Leary et al., 1999). When such narrowing of the arteries occurs in
the head, the condition is called intracranial atherosclerosis and is the dominant
cause of stroke in over 70% of the world‟s population (Kim, Caplan, & Wong,
2008).
Atherosclerosis and Stroke share many of the same risk factors including
those that are modifiable such as; high blood pressure, diabetes, hyperlipidaemia,
tobacco use, heavy alcohol consumption, obesity, physical inactivity and an
unhealthy diet, as well as non-modifiable factors including advancing age, gender
and a family history of early atherosclerosis (Blacker & Brown, 2002; Hobson,
Wilson, & Veith, 2004)
Atrial Fibrillation.
Of all the cardiac diseases atrial fibrillation is considered to be the most
powerful and treatable precursor of stroke. Atrial Fibrillation describes the rapid
irregular beating of the upper chamber of the heart which can result in slow blood
flow and the subsequent formation of blood clots. Anticoagulant and antiplatelet
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medications are often used to thin the blood and reduce the likelihood of clotting
which leads to stroke. Atrial fibrillation is known to rise markedly with
increasing age (Frost, Andersen, Godtfresden, & Mortensen 2007; Spence, 2006;
van Walraven et al., 2009; Wolf, Abbott, & Kannel, 1987) and has been well
identified as an independent risk factor for stroke (Kannel et al., 1981; Rastas et
al., 2007; Tsang et al., 2003; Wolf et al., 1987). A stroke may result when a blood
clot (embolus) breaks off, travels through the blood stream and lodges in the
artery leading to the brain. Atrial fibrillation has been estimated to increase the
risk of stroke about five-fold, particularly in the elderly in whom the prevalence of
atrial fibrillation is high (Lancaster, Mant, & Singer, 1997; Wolf, Abbott, &
Kannel, 1991). Data from the Framingham study also showed that ischaemic
stroke that occurred with atrial fibrillation is almost twice as likely to be fatal than
stroke without atrial fibrillation (Lin et al., 1996).
Diabetes.
Diabetes mellitus is a disorder of metabolism which results in the body
accumulating glucose in the blood. The excess glucose can then attach to proteins
in the blood vessels creating a build up of plaque which causes them to become
thicker and less elastic making it hard for blood to flow through. Diabetes has
been well established as a risk factor for stroke (Burchfield et al., 1994; Davis,
Millns, Stratton, Holman, & Turner, 1999; Goldstein et al., 2001; Lukovits,
Mazzone, & Gorelick, 1999; Manson et al., 1991), with several studies indicating
a two-fold increase of stroke risk with higher associated mortality and morbidity
(Abbott, Donahue, McMahin, Reed, & Yano, 1987; Jeerakathil, Johnson,
Simpson, & Majumdar, 2007; Kissela et al., 2005). Cubrilo-Turek (2004) suggests
that the population attributable risk for diabetes causing stroke is 15-20%.
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Furthermore, diabetic stroke patients have a worse prognosis than non-diabetic
stroke patients, with a two-fold increase in the likelihood of recurrent stroke.
While advanced age is the single most non-modifiable risk factor for stroke in the
general population, in patients with diabetes younger than 55 years, the risk of
stroke increases ten-fold (You et al., 1997). In their study of ischemic stroke
patients Kissela et al. (2005), found those patients with diabetes to be not only
younger than non-diabetic patients but also more likely to be African American,
to have hypertension, myocardial infarction, and high cholesterol. Indeed, people
with diabetes are often more susceptible to other stroke risk factors such as
hypertension, abnormal cholesterol levels, atherosclerosis and ischaemic heart
disease (Cubrilo-Turek, 2004; Lehto, Ronnemaa, Pyorala, & Laakso, 1996;
Lithner et al., 1998). Therefore, as well as management of blood glucose,
diabetes care needs to include management of blood pressure and cholesterol in
order to reduce the risk of stroke.
Migraine.
A number of studies have shown an increase in the risk of stroke among
people who have a history of migraine (Chang, Donaghy, & Poulter, 1999;
Connor, 1992; Dorfman, Marshall, & Enzmann, 1979; Tzourio, et al., 1995). This
association has been linked predominantly to migraine with aura (Bousser &
Welch, 2005; Diener & Kurth, 2005; Rothrock et al., 1993) although not always
(Carolei, Marini, & De Matteis, 1996). Some suggest that the relationship
between migraine and stroke is bidirectional, i.e. cerebral infarction can also cause
migraine (Bousser & Welch, 2005; Thomas, 2005). The mechanisms between
these two conditions is unclear as is the pathophysiology of migraine, however
one theory suggests that because migraine is essentially the result of
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haemodynamic changes within the brain, it is believed that stroke arises from
persistent decreased blood flow (Estol, 2001).
Another theory implicates Patent Foramen Ovale (PFO), (an incomplete
closure of the wall between the two upper chambers of the heart, also known as
“hole in the heart”), which is present in approximately 50% of individuals who
experience migraine with aura. The prevalence of PFO among stroke patients
with migraine associated with aura is also high (Mohammed, Ormerod, &
Downes, 2006). If the PFO is surgically closed the occurrence of migraine has
been shown to either cease or significantly reduce in intensity and frequency
(Jesurum et al., 2008; Sztajzel, Genoud, Roth, Mermillod, & le Floch-Rohr, 2002;
Tobis & Azarbal, 2005). The closure of the PFO prevents a clot that may have
formed in the vein from passing across the heart chambers into the arterial system
and travelling up to the brain where it may block a vessel and cause a stroke
(Rakhit, 2003).
Sickle cell anaemia.
Sickle cell disease is a heritable condition characterised by chronic anaemia
and episodes of pain. It is a blood disorder in which red blood cells mutate
assuming an abnormal rigid sickle shape. Although sickle cell disease is more
common in people of African and Mediterranean descent, it also presents in
people from South and Central America, the Caribbean and the Middle East (Lee
et al., 2006; WHO, 1996). Passage of cells through the blood vessels can become
difficult and the sickle cell may become jammed causing a blockage that impedes
the passage of oxygen and nutrients subsequently leading to stroke. The internal
carotid artery and the middle cerebral arteries are frequently affected and
commonly produce severe neurological deficits with even more disastrous results
247
in those who suffer recurrent strokes. Recent reports put the prevalence of stroke
in sickle cell disease as ranging from 4% to 8% (Balkaran et al., 1992; Johnson,
Unwin, & Graybeal, 2001; Ohene-Frempong, 1991). Approximately 10% of
children with sickle cell disease suffer a stroke making it the most common form
of stroke in children. 24% of patients with sickle cell anaemia will experience a
stroke by the time they are 45 years old (Switzer, Hess, Nichols, & Adams, 2001;
Wethers, 2000).
Ischaemic stroke is more common in children and older patients, whereas
haemorrhagic stroke has been found to occur more often in late adolescence and
early adulthood (Adams, 2001; Ohene-Frempong et al., 1998; Sarniak & Lusher,
1982, cited in Johnson et al., 2001). Death from cerebral infarction is rare
however haemorrhagic stroke are fatal in approximately 25% of those patients
with sickle cell anaemia (Switzer et al., 2001). Since the 1970‟s researchers have
been aware that patients who have suffered a stroke are at high risk of recurrence
and that chronic maintenance transfusion is highly effective in preventing that
recurrence (Josephson, Su, Hillyer, & Hillyer, 2007; Platt, 2006; Riddington &
Wang, 2002; Russell et al., 1984; Stockman, Nigro, Mishkin, & Oski, 1972).
Although there is no cure for this disease, it is nevertheless a treatable condition.
A healthy life style together with available treatments including pain
management, blood transfusions, and pharmaceutical interventions can help
people with sickle cell disease live with reasonably good health much of the time.
Behaviour/Lifestyle Changes
Tobacco.
Tobacco use is well established as a significant independent risk factor for
the occurrence of stroke (Center for Disease Control and Prevention. 2004;
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MacKay & Mensah, 2004; Manolio, Kronmal, Burke, O'Leary, & Price, 1996;
Wolf et al., 1988). The chemicals in tobacco smoke increase the build up of
plaque in artery walls and promote the development of blood clots that can cause
strokes. According to Cubrilo-Turek (2004), smoking doubles the risk of stroke
there is a clear relationship between the number of cigarettes smoked and the risk
of stroke. Kurth et al. (2003), provided evidence that smoking 15 cigarettes per
day increases the risk of stroke by up to four times. A number of researchers have
also found a positive correlation between the length of time smoking and
increased stroke risk (Adams, 2006; Bhat et al., 2008; Tamargo & Conway,
2006). As well as increasing the risk of ischaemic stroke, tobacco use has also
been demonstrated to increase the risk of subarachnoid haemorrhage (Isaksen,
Egge, Waterloo, Rommer, & Ingebrigsten, 2002; Qureshi et al., 2001) and
haemorrhagic stroke in both men and women (Kurth et al., 2003). The authors of
the American Heart Association and the American Stroke Association published
guidelines on the Primary Prevention of stroke in their systematic review of the
literature, associated cigarette smoking with a 2 to 4-fold increased risk of
haemorrhagic stroke (Broderick et al., 2003). They suggest that smoking
contributes to 12% to 14% of all stroke deaths. Second-hand smoking has also
been firmly established as contributing to the incidence of stroke (Bonita, Duncan,
Truelsen, Jackson, & Beaglehole, 1999; Glymour, DeFries, Kawachi, &
Avendano. 2008; You, Thrift, McNeil, Davis, & Donnan, 1999).
Alcohol.
Heavy drinking is associated with hypertension and atrial fibrillation and as
such alcohol has been correlated with increased risk of stroke (Furie & Kelly,
2004; Marmot & Poulter, 1992; Mukamala et al, 2005). However, research
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investigating a direct relationship between alcohol and stroke has produced mixed
results. In 1989, Gorelick failed to find any association between alcohol
consumption and cerebral infarction in middle-aged and elderly patients.
Conversely, other authors have found a positive relationship between heavy
alcohol consumption and increased risk for stroke (Caicoya, Rodriquez, Corrales,
Cuello, & Lasheras, 1999; Gill et al., 1991; Mohr, Choi, Grotta, Weir, & Wolf,
2004; Mukamala et al., 2005; You et al., 1997). A 2003 meta-analysis reviewing
35 studies indicated that >60 g of alcohol per day increased the risk of stroke
although light or moderate consumption, i.e. <24 g per day decreased the risk of
stroke when compared with abstainers (Reynolds et al., 2003). There has been
further evidence for an association between moderate consumption and a reduced
risk of stroke (Berger et al., 1999; Carmago, 1989; Elkind et al., 2006; Sacco et
al., 1999; Stampfer, Colditz, Willet, Spaizer, & Hennekens, 1988). Gill, Zezulka,
Shipley, Gill, and Beevers (1986), found those drinkers whose consumption was
10 to 90 g of alcohol weekly had a 0.5 lower relative risk of stroke than nondrinkers. In an epidemiological review of the literature Camargo (1989) reported
the same relationship in predominantly white populations however minimal
evidence of any such association was found within a Japanese population. There
is also evidence for an association between heavy drinking and an increased risk
of haemorrhagic stroke (Ebrahim et al., 2006; Iso et al., 2004) although Klatsky,
Armstrong, Friefman, and Sidney (2002) only found a weak correlation.
However, unlike the protective effect of moderate drinking for the risk of
ischaemic stroke, (Daniel & Bereczki, 2004), this did not appear to be the case for
the occurrence of haemorrhagic stroke. The association between heavy drinking
and subarachnoid haemorrhage has also been firmly established (Hillbom &
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Kaste, 1981; Juvela, Hillbom, Numminen, & Koskinen, 1993; Longstreth, Nelson,
Koespell & van Belle, 1992). There is a growing pool of evidence to suggest that
the type of alcohol consumed may alter stroke risk factors. For example, wine
may convey greater benefit than other type of alcohol (Malarcher et al., 2001;
Truelsen, Gronbaek, Schnohr, & Boysen, 1998). Mukamala et al. (2005) showed
that men who drank red wine had a 23 percent lower risk of a stroke compared
with those who drank other types of alcohol although further research was
recommended in order to validate their findings.
Physical Inactivity.
A clear association between physical inactivity and an increase in the risk of
stroke has been established (Abbot, Rodriquez, Burchfield, & Curb, 1994; Gillum,
Mussolino, & Ingram, 1996; Goldstein & Amarenco, 2005; Hu, Tuomilehto,
Silventoinen, Barengo, & Jousilahti, 2004). Several studies have also
demonstrated an inverse relationship between increased physical activity and
stroke risk factors such as hypertension, high cholesterol, obesity, diabetes and the
development of atherosclerosis (Gorelick & Alter 2002; Heart and Stroke
Foundation of Ontario website; Warburton, Nicol, & Bredin, 2006). There is
some evidence of a dose-response gradient of reduced stroke with increasing
activity (Dishman, Washburn, & Heath, 2004), although Kiely, Wolf, Cupples,
Beiser, and Kannel (1994), only found a protective effect of medium and high
levels of physical activity for males and not for the females in their study. A
meta-analysis of the literature covering 1966 to 2002 concluded that there was a
lower risk of both ischaemic and haemorrhagic stroke in moderate and highly
active individuals (Lee, Folsom, & Blair, 2003), a finding that was replicated in a
more recent meta-analysis of 31 observational studies (Wendel-Vos et al., 2004).
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Obesity.
The relationship between obesity and stroke remains controversial primarily
because of methodological inconsistencies across studies. Those studies using
Body Mass Index (BMI) as an indicator have wrongly included short wellmuscled individuals as overweight while other studies have used waist-to-hip ratio
as the indicator. Nevertheless, obesity and in particular abdominal adiposity and
waist circumference and the occurrence of ischaemic stroke have a positive
relationship (Godfrey & Sacco, 2009; Grau et al., 2001; Hu, 2008; Mohr et al.,
2004; Suk et al., 2003). The occurrence of stroke as a result of obesity is thought
to occur through the mechanics of hypertension and diabetes (Shinton, Sagar, &
Beevers, 1995). The implications of obesity for other stroke types also remain
unclear although Kurth et al. (2002) found a positive correlation between BMI
and occurrence of ischaemic and haemorrhagic stroke independent of confounding
risk factors such as hypertension, diabetes and high cholesterol. The World
Health Organisation warns against a potential surge in stroke incidence as the
obesity epidemic spreads across developed countries.
Diet.
Due to the association of diet with obesity and its complex interactions with
other lifestyle factors, e.g. people with nutritional diets tends to smoke less, it is
difficult to exactly determine the extent to which diet alters the risk of having a
stroke. A number of studies have demonstrated that healthy nutritional habits
play a significant role in mitigating other stroke risk factors including
hypertension, high cholesterol, diabetes and cardiac disease (Amarenco,
Labreuche, & Touboul, 2008; Spence, 2006). A Western style diet that is
typically high in fat, sugar and salt has been found to increase the risk of stroke
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(Metzger, Kotulak, & Brick, 2006) by raising triglycerides and increasing blood
pressure. Conversely, several studies examining diets that are low in saturated
fats and sodium and high in fruit and vegetables have been shown to significantly
reduce the risk of stroke (Dauchet & Dallongeville, 2008; Gillman et al., 1995;
Sauvaget, Nagano, Allen, & Kodama, 2003; Van Duyn & Pivonka, 2000). Fung et
al. (2009) found that the Mediterranean diet comprising of fresh fruit, an
abundance of plant foods, dairy foods (cheese and yoghurt), olive oil, moderate
amounts of fish and poultry, low amounts of red meat, zero to four eggs consumed
weekly and moderate amounts of wine, was associated with a lower risk of stroke
in women.
Research into diet and stroke subtype is scarce although there is some
evidence that consumption of baked or boiled fish is associated with a decreased
risk of ischaemic stroke (He et al., 2002; He et al., 2004). Mozaffarian et al.
(2005) had a similar outcome in their study investigating fish consumption in an
elderly population although in the same group they found that fish that had been
fried increased the risk of haemorrhagic stroke.
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Appendix B
Outcomes of Stroke
Survival
Survival from stroke is influenced by various factors including stroke
subtype, the extent of the neurological damage, level of consciousness; the
presence of cardiac disease, hypertension and diabetes; previous stroke history,
impact of disability, and level of supportive and rehabilitative care, to name a few
(Sacco, 2005; Williams & Jiang, 2000).
Survival rates for patients vary considerably between studies however the
greatest risk of death appears to occur in the first 30-days post-onset and is related
to type of stroke (Rundek & Sacco, 2004; Warlow, Dennis, van Gijn, Hankey, &
Sandercock, 2001). Fatality rates are greater for patients with intracerebral
haemorrhage than patients with cerebral infarction (Boden-Albala & Sacco, 2004;
Vernino et al., 2003; Wang & Talkad, 2009). In the Rochester study covering the
course of stroke from 1955 through to 1969, the overall 30-day survival rate was
72% (Matsumoto, Whisnant, Kurland, & Okazaki, 1973). The same survival rate
was found in an analysis of the Framingham study covering the years 1971
through 1981 (Kelly-Hayes et al, 1988) and in the Oxfordshire Community Stroke
Project, the overall stroke survival rate for the years 1981 through 1986, was 81%
(Bamford et al., 1990). In all three studies, survival rates for patients who
sustained an ischaemic stroke were considerably higher than those who had
suffered haemorrhagic stroke. In a recent systematic review of worldwide stroke
incidence and case fatality, 21-day to 1-month survival rates for all strokes in high
income countries for the period 2000 through 2008, was between 17 and 30% and
18 to 35% in low and middle income countries. Again, there was a significantly
254
higher fatality rate for haemorrhagic stroke than for ischaemic stroke (Feigin et
al., 2009).
Most recent studies have failed to establish a gender difference in both
short-term and long-term survival rates of stroke (Appleros et al., 2003; Carlo et
al., 2003; Glader et al., 2003; Terent, 2003). However, some studies have
demonstrated better survival rates for either men (Arboix et al., 2001) or women
(Andersen, Andersen, Kammersgaard, & Olsen, 2005; Niewada, et al., 2005;
Olsen, Dehlendorff, & Andersen, 2007).
The “clot busting” agent tissue plasminogen activator (tPA) has been shown
to be an effective treatment resulting in increased survival for ischaemic stroke
patients (Lansberg Bluhmki, & Thijs, 2009; NINDs, 1995; Marler, 2005;
Wardlaw, Lindley, & Lewis, 2002). However, there is a narrow 3 to 4.5 hour
time-to-treat window with greater benefits achieved the sooner the treatment takes
place (Hacke et al., 2004; Temporal, 2005). In a randomised double-blind trial of
291 ischaemic stroke patients who were given either tPA or a placebo, the former
group performed better at 3 months across four measures including the Barthel
Index, the Modified Rankin scale, The Glasgow Outcome Scale and the NINDS
(National Institute of Neurological Disorders and Stroke rt-PA Stroke Study
Group, 1995). These findings were replicated in a similar more recent study
providing further encouragement for the use of tPA for the treatment of acute
ischaemic stroke (Schmulling, Grond, Rudolf, & Heiss, 2000).
In a New Zealand study, improved technology and an increase in
hospital admissions were two factors credited for a rise in survival rates and
better outcomes for stroke patients in recent years, a trend that was observed
in the USA in the 1980s and in other developed high-income countries
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(Carter, Anderson, Hackett, Barber, & Bonita, 2007; Feigin et al., 2009;
Lakshninarayan, Anderson, Jacobs, Barber, & Luepker, 2009; McCarron,
Smith, & McCarron, 2006; Shahar et al., 1995).
Recurrence
Stroke recurrence rate is an important outcome measure, as patients
who suffer recurrent stroke have poorer outcomes than those with first-ever
strokes (Ng, Jung, Chiong, & Lim, 2007). A 10-year prospective study of
patients with suspected acute stroke or TIA, found the risk for recurrent
stroke to be 6 times greater compared to the general population (Hardie,
Hankey, Jamrozik, Broadhurst, & Anderson, 2004). Other authors have
suggested a stroke recurrent rate of 25% to 35% (Diller, 1999; Williams et
al., 1999) although most studies indicate variance at different stages poststroke. For example, large community-based studies have found recurrence
rates of stroke to be 1.7% to 4% in the first 30 days, from 6% to 13% in the
first year and from 5% to 8% per year for the next 2 to 5 years, with a
cumulative risk of 19 to 42% over the first 5 years (Petty et al., 1998; Sacco,
Shi, Zamanillo, & Kargman, 1994). Another study of patients on the South
London Stroke Register found the cumulative risk of stroke recurrence at 1
year, 5years and 10 years was 7.1%, 16.2% and 24.5%, respectively
(Mohan, Richton, Grieve, Wolfe, & Heuschmann, 2009). Furthermore,
mortality after recurrent stroke was found to be almost doubled compared
with patients with a first-ever stroke (Jerrgensen, Nakayama, Reith,
Raaschou, & Olsen, 1997). Although research into the risk for the
recurrence of stroke has produced contrary findings, largely because of
methodological differences, it is nevertheless evident that stroke recurrence
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is frequent and responsible for a major portion of overall stroke morbidity
and mortality (Sacco, 1994).
Studies comparing the recurrence of specific stroke subtypes found
that patients with atherothrombotic infarcts and cardioembolic stroke have a
higher risk of recurrence compared to patients who have suffered a lacunar
infarct (Hata et al., 2005; Modrego, Mainar, & Turull, 2004; Petty et al.,
2000; Sacco et al., 1989). For example, Modrego et al. (2004) found the
cumulative recurrence rates for atherothrombotic stroke at 1 month, 1 year
and 5 years to be 2%, 11% and 28% respectively; 3.5%, 12.5%, and 25% for
cardio-embolic stroke and 1.2%, 9%, and 22% for lacunar stroke. In their
longitudinal study of ischaemic stroke patients, Petty et al. (2000), estimated
rates of recurrent stroke at 30 days was 18.5% for athero-thrombotic stroke,
5.3% for cardio-embolic strokes and 1.4% for lacunar strokes. Two recent
studies found that patients with posterior circulation TIA or stroke, although
less common than stroke involving the anterior circulation, have a higher
recurrent stroke risk (Azarpazhooh et al., 2008; Gulli, Khan, & Markus,
2009).
Mohan et al. (2009) found that prior-to-stroke risk factors were also
significant determinants of recurrent stroke. Other risk factors associated
with greater recurrence of stroke include; previous TIA, atrial fibrillation,
ischemic heart disease, hypertension, and diabetes (Alter et al., 1987;
Yokota, Minematsu, Hasegawa, & Yamaguchi, 2004). Tatemichi et al.
(1993) also found the presence of cognitive impairment to be associated
with increased risk of recurrent stroke.
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It is critical that appropriate management of risk factors for recurrent
stroke are addressed soon after the event. A number of treatments have been
recommendation to reduce the recurrent of secondary stroke including,
placing all stroke survivors on aspirin or an alternate antiplatelet drug
(Norris, 2005) lowering blood pressure, treating hypertension, or placing the
stroke patient on statin therapy (Goldstein et al., 2009; PROGRESS
Collaborative Group, 2001; Sacco et al., 2006),
Stroke outcomes are largely determined by site and severity of the lesion
although many other variables such as age, co-morbidities, general well-being and
previous stroke history can also influence the effects of the stroke. The following
sections will provide a brief outline of the physical, perceptual, psychological or
behavioural effects of stroke?
Visual Field Deficits of Stroke
Homonymous Hemianopia.
Homonymous Hemianopia refers to partial blindness which results in
a loss of vision in the same visual field of both eyes and can arise out of
many types of injuries to the brain including tumour, trauma, infection,
epilepsy, arteriovenous malformation, or stroke, to name a few. However, it
is most commonly a neuro-ophthalmological manifestation of stroke (Gray
et al., 1989; Kelley & Kovacs, 1986; Peli, 2000; Rowe et al., 2009). This
condition which usually affects the peripheral vision, results in problems
with reading and visual scanning because people fail to notice stimuli in the
affected field. For example, a lesion of the right occipital lobe will affect
the left visual fields of each eye. It may also cause some individuals to run
into objects, trip or fall, knock things over, or be surprised by objects that
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seem to appear out of nowhere (Anderson, 2002). The ability to drive a
vehicle safely is compromised and indeed in some countries, individuals
with homonymous hemianopia are not legally able to do so.
In Australia, a study of the implications of post-stroke homonymous
visual field (PSHVF) loss for driving implications, found a prevalence rate
of 16% for homonymous visual field defects amongst sixty one stroke
patient admissions (Townsend et al., 2007). A more recent study in the UK
investigating the prevalence of visual impairment following stroke found
29.4% of their 323 study sample suffered homonymous hemianopia (Rowe
et al., 2009). Rossi, Kheyfets and Reding (1990), suggest as many as a third
of all stroke patients may suffer homonymous hemianopia. This disorder
has been found to have an adverse effect on recovery with considerable
social and vocational consequences (Kalra, Smith, & Crome, 1993).
Visual neglect is sometimes confused with homonymous hemianopia
as they are both visual deficits. However, the latter is a physical loss of
visual field to one side, while the former is a problem of inattention. The
patient may or may not suffer from homonymous hemianopia but due to the
visual neglect, cannot learn to compensate because they cannot mentally
attend to that side. An in-depth discussion of visual neglect is provided later
in this chapter in the section on attention deficits.
Diplopia.
Diplopia is the medical term for what is commonly known as double
vision (i.e., the individual sees two images of a single object at the same
time). The condition is not a problem with the mechanics of the eyes but
rather results from damage to those parts of the brain that control and co-
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ordinate eye movements. Aetiology of diplopia is wide and varied however,
sudden onset is typical when a person experiences a stroke that affects the
vertebrobasilar system which usually affects the brainstem, cerebellum, and
occipital lobe (Bogousslasky & Caplan, 2001). Diplopia may be
intermittent or constant, horizontal, vertical or tilted and may also be
distance dependent (Caplan, 2005; Stein, 2004; Warlow et al., 2001;
Wiebers, Feigin, & Brown, 2006). A number of authors have shown a high
incidence of visual disturbance, including diplopia, following stroke (Clisby
& Cox, 1999). This disorder can present considerable problems for
functional recovery. For example, Rathore, Hinn, Cooper, Tyroler, and
Rosamund, (2002), in their study of 474 confirmed stroke hospitalised
patients found a 5.5% occurrence of diplopia. Diplopia can be a major
handicap to good functional outcomes (Barker-Collo & Feigin, 2006).
Motor Deficits
Hemiplegia/Hemiparesis.
Hemiplegia refers to the total paralysis of the arm leg and trunk while
Hemiparesis is weakness of one side of the body. Both disorders affect the
contralateral side of the body to the brain lesion because the corticospinal tract
which runs down from the cortical neurons of the frontal lobe to the motor
neurons of the spinal cord crosses to the opposite side at the lowest point of the
medulla known as the pyramids. Hemiplegia is common following stroke,
occurring in as many as 75% to 88% of stroke survivors at 30 days with a high
incidence of associated neurological deficits in the acute stage (Diller, 1999).
Hemiparesis is also common with some authors estimating occurrence between
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80-90% of all patients with stroke (Bogousslavsky et al., 1988; Herman et al.,
1982; Libman, Sacco, Shi, Tatemichi, & Mohr, 1992)
Ataxia.
Ataxia is the term used to refer to a neurological deficit characterised
by a gross lack of muscle co-ordination manifested by disjointed or jerky
movements resulting in problems with walking or picking up objects.
Ataxia occurs as a consequence of damage to that part of the nervous system
that coordinates movement, such as the cerebellum (Timmann & Diener
cited in Bogousslavsky & Caplan 2001 p. 53). Speech, eye movement and
ability to swallow can also be affected by this disorder (Bendheim & Berg,
1981; Deluca et al., 2011).
Dysarthria.
Dysarthria is an acquired motor speech disorder characterised by
dysfunction in the initiation, control and co-ordination of those articulatory
structures involved in speech output. It is a clinical manifestation of
cerebral ischaemia and has been observed in 8 – 30% of all patients in a
large number of stroke studies (Urban et al., 2006). Dysarthria has been
identified with poorer outcomes following stroke (Tilling et al., 2001).
Dysphagia.
The initiation of swallowing is a voluntary action that involves the
integrity of the motor and sensory areas of both cortices while the reflexive
component of swallowing is mediated by swallowing centres in the brain
stem (Martin & Sessle, 1993; Miller, 1982; Singh & Hamdy, 2006).
Disruption or difficulty of the swallowing process is termed dysphagia. The
most common symptom of dysphagia post-stroke is difficulty trying to
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swallow, although other symptoms such as choking or breathing saliva into
the lungs while swallowing, coughing while or after swallowing,
regurgitating liquid through the nose, excessive throat clearing, breathing in
food while swallowing, weak voice and weight loss, may also be present
(Edmans et al., 2010). Disturbance of swallowing symptoms is related to
the neurological lesion site (Steinhagen, Grossman, Benecke, & Walter,
2009).
The incidence of dysphagia following stroke is high (Bougousslavsky
& Caplan, 2001; Gordon, Hewer, & Wade, 1987; Langdon, Lee, & Binns,
2007; Mann, Hankey, & Cameron, 2000; O‟Neill, 2000; Martino et al.,
2005). In their systematic review of the literature Martino et al. (2005)
found that the frequency of dysphagia following stroke, ranged from 37% to
as high as 78% with higher rates detected when more accurate instrumental
screening tools, as opposed to clinical assessment, were used. Different
inclusion criteria across studies also impacted on the rates of dysphagia
found across studies. Recovery time from dysphagia depends on numerous
factors including severity and site of the lesion, comorbidities, assessment
protocols and treatment regimes. Although symptoms will often resolve in
the acute stage of recovery, dysphagia has also been found to be a predictor
of delayed recovery, poorer outcomes and serious complications such as
aspiration pneumonia. (Foley, Teasell, Salter, Kruger, & Martino, 2008;
Langdon et al., 2007; Mann, et al., 2000; Martino et al., 2005; Obara,
Tomite, & Doi, 2008; O‟Neill, 2000; Sharma, Fletcher, Vassallo, & Ross,
2001; Singh & Hamdy, 2006; Smithard et al., 1996).
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Aspiration pneumonia.
Aspiration pneumonia is a lung infection caused by the inhalation of
foreign material into the lungs. These tiny particles are normally prevented
from entering the airways by a complex physiological mechanism which is
compromised in the patient with dysphagia thus allowing oral contents to
drop into the trachea and then into the lungs. The contaminated contents
enter the more sterile environment of the lungs causing infection and
inflammation (Kaste & Roine, 2004; Marik, 2001; Mohr et al., 2004;
Speiker, 2001). Stroke survivors who are diagnosed with aspiration
pneumonia have an increased risk of dying when compared to patients who
do not have pneumonia (Hreib, 2008; Meng, Wang, & Lien, 2000; Reynolds
et al., 1998), however studies have shown a number of protective measures
such as early assessment, improved oral and dental care, positioning of
patients, treatments of reflux, unidirectional speaking valves and nasogastric
feeding as been effective in reducing the risk of aspiration pneumonia
(Drakulovic et al., 1999; Jones, 1993; Mamum & Lim, 2005; Marik &
Kaplan, 2003; Terpenning et al., 2001; Ramsey, Smithard, & Kalra, 2003;
Rhinehart & Friedman, 2005; Sarin, Balasubramaniam, Corcoran,
Laudenbach, & Stoopler, 2008).
Verbal Deficits
Aphasia.
The term aphasia literally means “complete loss of language” however
in most cases of neuropsychological impairment some linguistic abilities are
retained and therefore “dysphasia” meaning a “partial lack of language”, is a
more accurate term for use (Sims, 2003). Disturbance in comprehension or
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production of spoken written or signed language are the hallmarks of this set
of disorders. Locating specific areas of the brain in relation to aphasic
symptoms has been problematic as the production and comprehension of
language depends on a complex and dynamic interaction between vast
regions of the brain. Nevertheless, damage to particular cortical regions, has
been found to produce a cluster of aphasic symptoms. Broca‟s Area, sited in
the left frontal lobe and Wernicke‟s Area sited in the left temporal lobe have
long been known as the major areas of the brain responsible for language.
The group of fibres running deeply into the white matter of the temporal,
parietal, and frontal regions that connect these two areas is known as the
arcuate fasciculus (Bruni & Montemurro, 2009; Eysenck & Keane, 2000).
More recently, a third area named Geschwind‟s territory, which
connects Broca‟s and Wernicke‟s areas via a region of the parietal cortex has
been identified as playing an important role in language acquisition in
children. These areas are found in the left hemisphere of 99% of righthanded people and 60-70% of left-handed people, which is dominant for
language (Ganong, 2005; Roth & Heilman, 2000).
The four general types of aphasia are; Broca‟s Aphasia, Wernicke‟s
Aphasia, Anomic Aphasia, and Global Aphasia. Stroke is the most common
cause of aphasia (Kirshner, 2004; Ruiz, 2000; Wade, Hewer, David, &
Enderby, 1986), although some other events that can cause lesions leading
to aphasia are traumatic brain injury, degenerative neurological disease, and
certain chronic neurological disorders such as migraine, epilepsy, or brain
tumour.
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Although the prevalence and course of post-stroke aphasia is
dependent on the diagnostic criteria and the time of first evaluation, research
estimates the incidence of aphasia post-stroke as varying from 17% to 40%
(Hier, Yoon, Mohr, Price, & Wolf, 1994; Nicholas, 2005; Pedersen,
Jorgensen, Nakayama, Raaschou, & Olsen, 1996). Typically, patients with
Broca‟s aphasia fully understand spoken and written language however, are
unable to speak fluently themselves even though they know what they want
to say. There is a delay in the formation of sentences which are often
delivered as broken phrases or with words often been communicated one at
a time. There is diminished vocabulary, and speech lacks correct
grammatical conventions and there is particular difficulty using adverbs and
prepositions. Stress patterns and intonation are absent so the individual
speaks in a flat and mono-pitched tone (Dronkers & Larsen, 2001).
Primarily, people who suffer from Wernicke‟s aphasia have difficulty
understanding the speech of others including simple and complex
statements. They cannot follow directions or answer questions. For
example, if you are having coffee with a patient and you ask for the sugar,
the patient may not respond or may pass you the cream. However, patients
with Wernicke‟s aphasia can also have problems expressing themselves and
their speech may be characterised by the use of jargon, that is, the words
they use have the wrong or no meaning at all (Tanner, 2007). These
Wernicke‟s patients suffer greater disability than sufferers of Broca‟s
aphasia only.
Global aphasia, caused by lesions to both Broca‟s and Wernicke‟s
areas results in the patients experiencing significant difficulty in all
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modalities of language both spoken and written. This condition is most
prevalent after strokes that have involved the internal carotid artery or the
middle cerebral arteries (Ozeren, Koc, Demirkiran, Sonmezler, & Kibar,
2006).
Word finding difficulty is a problem present in a number of aphasias
however when this deficit occurs in isolation, the term “Anomic aphasia” is
applied (Schwartzman, 2006). Preservation of speech characteristics and
auditory comprehension remain intact. Many patients present with specificcategory naming deficits, for example difficulty with verbs and not nouns or
the reverse. Other patients may have difficulty naming animate objects but
not inanimate objects (Benson & Ardilla 1996; Nicholas, 2005).
The type of aphasia presenting in the acute stage of stroke was
investigated by Croquelois Godefroy, and Bogousslavsky (2007). They
concluded that Global aphasia and unclassified aphasias (mainly anomic
plus aphasia of mild severity) accounted for half of the aphasic syndromes
while Wernicke‟s and Broca‟s aphasia accounted for 40%.
In two recent studies, gender was not found to be an independent
determinant in the presentation of aphasia post-stroke (Engelter et al., 2006;
Law et al., 2009; Pedersen, Jorgensen, Nakayama, Raaschou, & Olsen,
1995), however Kyrozis et al. (2009) found female gender to be an
independent prospective predictor of post-stroke aphasia. In two other
studies evidence for an anterior-posterior difference of extension of lesion
was found between women and men (Hier et al., 1994; Lang & Moser,
2003). The role of gender as an independent factor of aphasia post-stroke
remains unclear and debatable.
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Perceptual Deficits
Apraxia.
Apraxia is a neurological disorder usually associated with lesions to
the left cerebral hemisphere, affecting the ability to plan the steps involved
in a complex task and carry out those steps in the correct sequence despite
having the desire and physical ability to do so (Roth & Heilman, 1997). For
example, when a person is asked to pretend to blow out a match”, they fail
to do so, but when a lit match is placed before them they blow it out
successfully because the presence of the lit match “made it possible to
retrieve the movement memories” (Roth & Heilman, 1997, p. 1). Apraxia
presents on a continuum of severity and the milder forms of this disorder are
referred to as dyspraxia.
Neuropathology of apraxia as a consequence of stroke suggests that
lesions that occur in the left hemisphere are the most common cause of this
disorder (Duffy, 2005). It has been found to be a persistent disorder with
adverse effects on recovery of activities of daily living (Donkervoort,
Dekker, & Deelman 2006). Frequency of apraxia in post-stroke patients
differs considerably between studies. One reason for this disparity is
because subtle apraxic impairments have not been detected resulting in an
underestimation of the presence of this condition. For example, in one
study (Haaland & Flaherty, 1984), only 13% of the sample group were
found to have apraxia however, in another study (Schnider, Hanlon,
Alexander, & Benson, 1997) that used more sensitive measures, 45% of the
sample group fell into the apraxia range.
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Behavioural Outcomes
Fatigue.
After a stroke, many people feel unusually tired because of the extra energy
they use to cope with physical and emotional changes. However post-stroke
fatigue is more than just common tiredness, as expressed by Barker-Collo, Feigin,
& Dudley (2007, p.1), who consider post-stroke fatigue (PSF), to be “a complex
interaction of biological, psychosocial, and behavioural phenomena”. Staub and
Bogousslavsky (2001), propose a concept that links PSF to attentional deficits and
involves damage to structures involved in the subcortical attentional network.
Other common causes of fatigue include; pain, disease, anaemia, inactivity or
other health problems (Glaus, Crow, & Hammond, 1996). Whatever the
aetiology, fatigue is reported as persisting for months and even years after the
stroke.
Prevalence of fatigue in stroke patients is known to be high although the
lack of a common definition, different sample populations and the use of a wide
variety of assessment tools, has resulted in considerable variance across studies.
However, increased fatigue has been associated with insititutionalisation and casefatality and decreased functional independence (Glader, Stegmayr, & Asplund,
2002). Furthermore, PSF has been shown to have a detrimental effect on
rehabilitation, quality of life and returning to work and correlates significantly
with functional disability and neuropsychological deficits (Glader et al., 2002;
Ingles, Eskes & Phillips, 1999; Michael, 2002). Given that the causes of PSF are
multi-factorial it has been suggested that strategies to alleviate this problem need
to be individualised (Choi-Kwon, Han, Kwon, & Kim, 2005; Staub &
Bogousslavsky, 2001).
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Incontinence.
The incidence of urinary incontinence (UI), among survivors of stroke is
high and has found to be associated with the size of the infarct or cerebral
haemorrhage and severity of the stroke (Brittain et al., 2006; Brittain, Peet, &
Castleden, 1998; Brocklehurst, Andrews, Richards, & Laycock, 1985; Gelber,
Good, Laven, & Verhulst, 1993). Prevalence studies of UI in the acute stages poststroke have produced rates ranging from 32% (Kamouchi et al., 1995; Patel,
Coshall, Rudd, & Wolfe, 2001), to as much as 83% (Luft & Vriheas-Nichols,
1998). However, the transient nature of incontinence was demonstrated in
Nakayama, Jorgensen, Pedersen, Raaschou, and Olsen (1997) who found that the
majority of patients gained bladder control within 6 months post-stroke. This
transiency was again demonstrated in a 2-year study where Patel et al. (2001),
found the incidence of UI in their population at the acute stage, 3 months, 1 year
and 2 year post-stroke to be, 40%, 19%, 15% and 10%, respectively. In a review
of the prevalence of incontinence studies ranging from 1985 to 2002, Barrett
(2002), the improvement of incontinence over time is said to have been clearly
demonstrated.
Stroke patients who suffer from UI have a higher risk of mortality,
morbidity and a high rate of discharge to nursing homes (Brittain et al., 1998;
Kolominsky-Rabas, Hilz, Neundoerfer, & Heuschmann, 2003; Patel et al. 2001;
Thom & Van Den Eeden, 1997). Its presence is used as a prognostic factor for
stroke patients (Hamann, Rogers, & Addington-Hall, 2004; Kobayashi, Hara, &
Morita, 2005; Mant, Wade & Winner, 2004; Wade & Hewer, 1985) although as
Shuji, Mizuho, and Akiko (2005) point out the changing condition of the
incontinence needs to be considered when predicting outcomes. Effective
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treatment of UI has the potential to improve participation in rehabilitation and
ultimately the outcomes of rehabilitation. Early assumption of the standing
position and early ambulation promotes continence (Taub, Wolfe, Richardson, &
Burney, 1994). Other treatments commonly utilised for this condition include
pelvic floor muscle training, timed voiding, pharmacotherapy and hormonal
interventions and specialised professional input (Thomas et al., 2007).
Studies published in 1987 and 1997 found that between 31% and 40% of
stroke patients experienced fecal incontinence on admission to hospital (Brittain et
al., 1998; Nakayama et al., 1997; Wade & Hewer, 1987). Functional limitations
and age have been found to influence the presence of fecal incontinence (Brittain
et al., 2006; Kovindha, Wattanapan, Dejpratham, Permsirivanich, &
Kuptniratsaikul, 2009) although in one study age was not found to be a significant
factor (Edwards & Jones, 2001). Fecal incontinence is also negatively associated
with mortality and institutionalisation as well as having a detrimental influence on
functional outcomes (Baztan, Domenech, & Gonzalez, 2003).
Double Incontinence.
Double Incontinence is also commonly present after stroke. In one study
double incontinence was more prevalent than either urinary or fecal incontinence
alone (Kovindha et al., 2009), although in a postal survey of stroke survivors,
4.3% reported double incontinence as opposed to 5% with major fecal
incontinence alone (Brittain et al., 2006). However, the same study found double
incontinence to be four times greater in stroke survivors than in the general
population.
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Pain.
Pain is a frequent and often long-term consequence of stroke occurring in 19
to 74% of stroke patients (Henon, 2006; Kim, 2009; Milani, 2009), often having a
profound effect on patient‟s well-being. A recent study reported one third of their
patients suffered from moderate to severe pain 4 months after onset and that the
intensity of the pain had increased over time (Henon, 2006). The persistency of
this condition has been shown in other studies (Widar, Samuelsson, KarlssonTivenius, and Ahlstrom (2002) where intramuscular electrical stimulation
treatment was shown to be less effective when administered later rather than
earlier post-stroke (Chae et al., 2007). In another recent study, although the
number of patients experiencing pain at 4 and 16 month intervals dropped from
32% to 21%, the pain intensity was reported as being more severe at the later
interval (Jonsson, Lindgren, Hallstrom, Norrving, & Lindgren, 2005). Other types
of pain can be traced to nerve damage, bed sores, or a joint that doesn't move.
Central post-stroke pain (CPSP) also referred to as thalamic pain or
neurogenic pain, is a syndrome characterised by pain in the part of the body
corresponding to the brain territory where the lesion has occurred. CPSP occurs
most frequently following strokes on the right side of the brain, affecting the left
side of the body. Approximating the prevalence of CPSP is difficult partly due to
the difficulty in distinguishing it from other pain types that occur post-stroke (Klit,
Finnerup & Jensen, 2009) although between 8% and 14% prevalence rates have
been quoted by some authors (Bowsher, 2001; Kumar, Kalita, Kumar, & Misra,
2009).
Shoulder pain is also a common consequence of stroke especially in patients
with severe sensorimotor deficit (Ratnasabapathy et al., 2003). Two prospective
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studies demonstrated an incremental increase of incidence of shoulder pain in
their study sample over the first 6 months post-stroke (Langhorne et al., 2000;
Ratnasabapathy et al., 2003). A more recent study revealed 52% of the sample of
122 stroke survivors suffered shoulder pain over 12 months. The authors suggest
that such a high percentage of individuals were identified because, unlike previous
studies, their study did not exclude patients with language or cognitive
impairment (Sackley et al., 2008).
Emotional Lability.
Emotional lability is the term used to describe the very common effect
where stroke survivors lose control over their emotions (Horrocks, Hackett,
Anderson, & House, 2004). About 20% of stroke patients are believed to suffer
from this syndrome, which has a number of characteristic features including
feeling angry or irritable with little provocation or sudden and unexpected
episodes of laughing or crying that do not correspond to the underlying emotional
feeling (House, 1987; Robinson, 1997). Emotional lability may co-exist with
depression and according to Starkstein and Robinson (2000), patients respond
well to tricyclic antidepressants. In their systematic review of the literature,
Horrocks et al. (2004), found evidence to suggest pharmacological intervention
reduces crying emotionalism post-stroke. The authors however are guarded of the
findings citing vast methodological differences as having a negative effect on the
validity of their findings.
Anxiety.
Anxiety post-stroke is common and has a negative impact on rehabilitation,
daily functioning and quality of life in general (Fruhwald, Loffler, Eher, Saletu, &
Baumhackl, 2001; Kumar, Lavretsky, & Haroon, 2005; Sagen et al., 2009; Tanner,
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2007). In 2007, Barker-Collo, found 21.1% of her sample of stroke patients from
an inpatient rehabilitation unit suffered from anxiety, a result which is consistent
with other studies examining the frequency of post-stroke anxiety PSA (Castillo,
Starkstein, Fedoroff, Price, & Robinson, 1993; De Wit et al., 2008; Leppavuori,
Pohjasvaara, Vataja, Kasate, & Erkinjumtti, 2003; Robinson, 1998).
In their longitudinal study, Morrison, Pollard, Johnston, and MacWalter
(2005), found PSA to be present at 10-20 days, 1 month, 6 months and 3 years
after the stroke to be more common amongst females. This relationship is not
uncommon as suggested by a number of other studies that have also found a
higher correlation between PSA and being female than between PSA and being
male (Kadojic et al., 2005; Kuroda, Kanda, & Sakai, 2006; Wilz & Kalytta, 2008).
Current data about the relationship of anxiety with location site are not conclusive
although some studies have implicated the right hemisphere (Astrom, 1996;
Astrom, Adolfsson, & Asplund, 1993; Barker-Collo, 2007) while other studies
indicate left hemisphere involvement when the anxiety is comorbid with
depression (Castillo et al., 1993; Robinson 2006).
Depression.
A significant portion of stroke survivors experience psychological sequelae
which can include anxiety, depression, grief reaction, irritability, sadness or
unhappiness (Barker-Collo, 2007; Burvill et al., 1995; Ebrahim, Barer, & Nouri,
1987; Newberg, Davydow, & Lee, 2006: Saxena, 2006). Studies investigating
post-stroke depression (PSD) have produced a wide range of prevalence rates.
For example, Robinson (2003) in a summary of studies examining the prevalence
of stroke, found between 14% and 19% of individuals experienced PSD as
opposed to 10% in the general population. An earlier review of studies identified
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as many as 65% of stroke survivors suffer from PSD (Primeau, 1988). However,
prevalence rates between 20% and 50% have been found in most studies on this
issue (Barker-Collo, 2007).
Some authors report a correlation between people suffering PSD and
increased fatality (Bogousslavsky, 2003; Burvill et al., 1995; Feigin, 2004; Morris,
Robinson, Andrezejewski, Samuels, & Price, 1993; Morris, Robinson & Samuels,
1993; Paul, Srikanth & Thrift, 2007; Williams, Ghose, & Swindle, 2004). The
relationship between site of lesion and the incidence of PSD gravitates towards a
link with left hemisphere lesion (Barker-Collo, 2007; Morris, Robinson, &
Raphael, 1992; Starkstein, Robinson, & Price, 1987; Sulaiman, Zainal, Tan, &
Tan, 2002). A meta-analysis of 52 studies found a weak relationship between
right hemisphere lesion and PSD (Yu, Liu, Chen, Wang, & Yu, 2004).
Conversely, Vataja et al. (2005), found that a brain infarct affecting
structures of the frontal-subcortical circuits, especially on the left side, predispose
stroke patients to depression. Indeed, there is compelling evidence associating
PSD with left-hemispheric damage (Astrom et al., 1993; Barker-Collo, 2007;
Herrmann, Bartels, Schumacher, & Wallesch, 1995; Hosking, Marsh, & Friedman,
2000; Jorge, Robinson, Starkstein, & Arndt, 1993).
A temporal association between lesion location and PSD has also been
found by Shimoda and Robinson (1999) and Bhogal, Teasell, Foley, and
Speechley (2004). These findings suggest that individuals may experience PSD
symptoms immediately after the stroke as a sequeale of neurological alteration or
at a later stage, as a psychological development as their awareness of the impact
of the stroke increases. The substantial discrepancy in the findings regarding the
association between lesion location and PSD can be largely attributable to
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methodological procedures. Patient selection (in-patient or out-patient), time
since onset and the assessment of depression tools to measure post-stroke
depression have all contributed to the heterogeneity of the findings (Bhogal et al.,
2004; Toso et al. 2004).
The effects of PSD are widespread and are considered by some to be the
strongest predictor of quality of life in stroke survivors (Kim, Warren, Madill, &
Hadley, 1999; King, 1996). Moreover, PSD has been associated with increased
disability (Kotila, Numminen, Waltimo, & Kaste, 1999; Pohjasvaara, Vataja,
Leppavuori, Kaste, & Erkinjuntti, 2001), increased risk of falls (Jorgensen,
Engstad, & Jacobsen, 2002) and with worse rehabilitation outcomes (Gillen,
Tennen, McKee, Gernert-Dott, & Affleck, 2001; Paolucci et al., 1999; Sinyor et
al., 1986).
There is a large body of compelling evidence that PSD is associated with
cognitive impairment (Kauhanen et al., 1999; Murata, Kimura, & Robinson, 2000;
Narushima, Chan, Kosier, & Robinson, 2003; Robinson, Bolla-Wilson, Kaplan, &
Lipsey, 1986; Saxena, 2006; Talelli et al., 2004; Yoo, Jeong, & Kim, 2009) and
linked to left hemispheric lesion (Barker-Collo, 2007; Robinson et al., 1986;
Robinson, Kubos, Starr, Rao, & Price, 1984). Studies investigating the
relationship between PSD and specific cognitive functions have implicated
memory, non-verbal problem solving, attention and psychomotor speed (BarkerCollo, 2007; Hoskings et al., 2000; Kauhanen et al., 1999), visual perception and
construction, and language (Nys, 2005).
275
Appendix C
Participant Information Sheet
Clinical Trials
Research Unit
The University of Auckland
Tamaki Campus
Private bag 92019
Auckland
NEW ZEALAND
Telephone 021 164 9453
Facsimilie: 64 9 373 1710
Email: [email protected]
www.ctru,auckland.ac.nz
Project Title: Does Attention Process Training improve functional outcomes of
stroke?
Principal Investigator: Dr Suzanne Barker-Collo at the Department of
Psychology, The University of Auckland, Private bag 92019, Auckland (email:
[email protected]; phone 373-7599 extension 86875).
An invitation...
You are invited to take part in a new research study called:
“Stroke Attention Rehabilitation Trial (START)”
We would welcome your help in this important project, however, your
participation us entirely voluntary (your choice).
What is the purpose of the study?
The purpose of this study is to evaluate a new therapy called „Attention Process
Training‟ or APT as a form of rehabilitation for stroke survivors. If you have
experienced a stroke within the past 4 weeks, you may be able to join this study.
Why do we need this study?
The most common cognitive problem after stroke is reduced attention. A
reduction in the ability to pay attention may have a negative impact on a person‟s
ability to function and on their quality of life. A new form of rehabilitation to
address attention difficulties after stroke has been developed. It is called
„Attention Process training‟ or APT. We do not know if APT does improve
attention and function of people who have experienced a stroke.. and so we will
be testing APT in this study. This study will examine the effectiveness of
Attention Process training (APT) by comparing persons who have recently
suffered a stroke who receive APT with persons who have recently suffered a
stroke and receive usual care.
276
What is Attention Process Training?
APT is a comprehensive programme specifically designed to treat impairments in
paying attention. It is a series of tasks delivered by a trained neuropsychologist
using a paper and pencil or an audio tape. Each paper/tape contains exercises and
activities to be completed by the stroke survivor, to retrain the stroke survivor on
how to pay attention. The exercises are tailored to meet the ability of the stroke
survivor. If you are randomised to the group that receives the Attention Process
Training, the session will take one and a half hours, Monday to Friday for 4
weeks. This is flexible based on your health, and you will be allowed the
opportunity to rest if you wish too. The training will begin in hospital, and if you
are discharged prior to the training being completed, it will continue at your place
of residence.
Who can participate in this study?
People who have experienced a stroke within the past 4 weeks and have been
assessed as having a decrease in their ability to pay attention. We will be seeking
169 stroke survivors for this study.
What is involved?
If you decide that you would like to take part, you will undergo an initial
interview at hospital with a researcher who is a neuropsychological trainee or
neuropsychologist, to assess if you have a decrease in your ability to pay attention
and if you are well enough to complete the APT programme. If they are willing,
we will also be asking questions from the caregiver (family member or friend)
who provides you with the most support.
You will be required to complete a questionnaire and a series of tests with a
researcher to assess your cognitive functioning (ability to pay attention), current
state of health and your medical history. The initial interview will take about 30
minutes. We will also seek permission to access your medical and hospital records
to collect information on your medical history, the medications you are taking,
and the type of therapies you have received. If you are eligible for the study, you
will have three assessments: on the day of enrolment into the study, and then after
5 weeks, and at 6 months. The assessment at 5 weeks is similar to the initial
interview, and will take about 30 minutes.
For the assessment on the day of enrolment and at 6 months, you will be required
to complete a more extensive set of tests with a researcher to assess your cognitive
functioning (ability to pay attention, solve problems and remember things), and
questionnaires about your current state of health, your medical history, your
ability to do everyday things and your quality of life. The assessment will take
about 150 minutes, and you will have an opportunity to rest if you require it.
What is meant by the term „randomisation‟
If you agree to be part of this study you will be randomised either to receive the
Attention Process Training, or usual care rehabilitation. Randomisation is like a
flip of a coin, you have an equal chance that you will be in either the Attention
Process Training Group or receiving standard care. Currently, we do not know
which health service is the most effective for stroke rehabilitation; which is why
277
we are conducting the study. Randomisation allows us to compare the two
services with other.
What is APT?
Attention Process Training is a rehabilitation package used to improve difficulties
with attention. It includes a number of activities which get more difficult over
time. The program activities are not functional and resemble laboratory tasks, for
example listening to a list of words and pressing a button every time you hear the
word “and”. Participants in the APT group will receive daily individual APT
treatment on weekdays for a period of 4 weeks.
What are the expected benefits?
You may not directly benefit from the study, as we do not know if APT works.
However, you will help the people who fund, provide and deliver health services
for stroke rehabilitation. This study will be of benefit to the wider population.
There is no guarantee that you will benefit directly from being involved in this
study.
What are the potential risks and discomforts?
Taking part in this study will take some of your time and require you to answer a
series of questions. There are no known risks caused by this study. As we are
only asking questions and getting you to perform mental tasks, there are no risks
with this study. You may find some of the tasks tiring, but can take a break at any
time. You will not be asked to perform any tasks that make you feel
uncomfortable or that you do not feel that you can complete. You will continue to
receive care from your doctor and other health services. Your usual medical care
will not be affected in any way by participating in this study, or by declining to
participate or withdrawing from the study at any stage. Your participation in this
study will be stopped should any harmful effects appear or if the doctor feels it is
not in your best interest to continue. Similarly your doctor may at any time
provide you with any other treatment he/she considers necessary.
Confidentiality
All data generated from this study will be treated with utmost confidentiality
without reference to your name. It is very important that the data collected are
accurate and therefore, it will need to be checked against your medical records.
You are therefore asked to give permission for the researchers to look at your
medical records to help them carry out these checks and to access information on
what health services you receive during the trial from the District health Board
and their agencies. Naturally, the information will be kept strictly confidential
and will be used only for statistical purposes of this study. Your identity will be
kept confidential. In the study documents you will only be identified by your
initials, date of birth, and a study number. The data will be kept for the duration
of the study at the Clinical trials Research Unit, The University of Auckland and
destroyed after 16 years according to national research guidelines. Any
information provided to interviewers will not be acted upon unless there are
concerns about the participant‟s safety or the safety of others.
278
Withdrawal from the study
Your participation in the study is entirely voluntary. You may withdraw at any
time, and you do not have to give a reason for doing so, although it would be
helpful if you did and to participate in the final assessment visit if at all possible.
Your doctor may also suggest that you withdraw if he/she has any concerns about
your participation. You may also be withdrawn if you are not able to comply with
the study procedures or for other administrative reasons. If you do withdraw, this
will in no way affect any future treatment you may require.
Costs
There will be no charge made to you for any attendance or tests conducted during
this study. Your doctor will not be paid or incur and study related costs for your
participation.
Compensation for Physical injury
In the unlikely event of a physical injury as a result of your participation in this
study, you may be covered by ACC under the Injury Prevention, Rehabilitation
and Compensation Act. ACC cover is not automatic and your case will need to be
assessed by ACC according to the provisions of the 2002 Injury Prevention
Rehabilitation and Compensation Act. If your claim is accepted by ACC, you still
might not get any compensation. This depends on a number of factors such as
whether you are an earner or non-earner. ACC usually provides only partial
reimbursement of costs and expenses and there may be no lump sum
compensation payable. There is no cover for mental injury unless it is a result of
physical injury. If you have ACC cover, generally this will affect your right to
sue the investigators.
If you have any questions about ACC, contact your nearest ACC office or the
investigator.
Further Information
You are encouraged to ask questions at any time during the study. If you have
any questions at any time during the study please do not hesitate to ask your
general practitioner or the research staff associated with the study.
If you have any queries or concerns regarding your rights as a participant in this
study you may wish to contact a Health and Disability Advocate on 0800 423 638
Northland to Franklin – free fax 0800 2787 7678.
You will receive a copy of this information sheet. If you want more
information, please contact either the Principal Investigator Dr Suzanne
Barker-Collo at the Department of Psychology, University of Auckland on 09
373-3=7599 ext 88517 or Ms Margaret Dudley on 021 164 9453.
This study has received ethical approval from the Northern X Regional Ethics
Committee.
279
Appendix D
Consent Form
Clinical Trials Research Unit
The University of Auckland
Tamaki Campus
Private bag 92019
Auckland
NEW ZEALAND
Telephone 021 164 9453
Facsimilie: 64 9 373 1710
Email: [email protected]
www.ctru.auckland.ac.nz
Project Title: Does Attention process Training improve functional outcomes of
stroke?
Contact
Margaret Dudley
Clinical Trials Research Unit
The University of Auckland
Private Bag 92019
Auckland
Ph 021 164 9453
CONSENT FORM
Registration Number
_________________
English
Maori
Samoan
Tongan
Cook
Island
Niuean
I wish to have an interpreter
E hiahia ana ahau ki tetahi tangata hei korero Maori
ki ahau
Oute mana‟o e iai se fa‟amatala upu
„Oku fiema‟u ha fakatonulea
Ka inangaro au i tetai tangat uri reo
Yes
Ae
No
Kao
Loe
Lo
Ae
Leai
Ikai
Kare
Fia manako au ke fakaaoga e tagata fakahokohoko
vagahau
E
Nakai
280
I,_________________________________________________, acknowledge that
I have had explained to me by the Neuropsychologist Trainee, the nature and
procedures involved with this research study.
I have read and I understand the information sheet dated 24/08/2006 for
volunteers taking part in the study designed to evaluate the effects of Attention
process Training on stroke survivors.
I have had the opportunity to discuss this study. I am satisfied with the answers
that I have been given.
I‟ve had the opportunity to us whanau support or a friend to help ask questions
and understand the study.
I understand that taking part in this study is voluntary (my choice) and that I may
withdraw from the study at any time and this will in no way affect my future and
continuing health care.
I understand that my participation in this study is confidential and that no material
which could identify me will be used in any report on this study.
I am aware that the exception to confidentiality will be applied in situations where
the interviewer has significant concerns about the safety of myself or others.
I understand the compensation provisions for this study.
I have had time to consider whether to take part.
I know who to contact if I have any problems from taking part in this study.
I know who to contact if I have any questions about the study.
I give consent for the researchers to access my medical records and information
on the health services I receive during the study from the health service funder or
provider YES/NO
I would like to receive a copy of the results of the study YES/NO
I consent to take part as a subject in this research YES/NO
281
Signature________________________________________________________
Date_________/__________/__________
Project explained by________________________________________________.
282
Appendix E
Tables showing correlations between baseline and post-intervention
measures with the highest tasks reached on APT.
Table E-1
Correlations between baseline demographics and highest auditory and
visual task reached
Baseline
Demographic
Age
Gender
Education
Time since stroke
MMSE
Barthel Index
Highest Auditory Task
Highest Visual Task
0.26
-0.25
-0.09
-0.12
-0.20
-0.18
-0.04
0.01
0.07
-0.12
-0.22
-0.27
Table E-2
Correlations between baseline attention measures and highest auditory and visual
task reached
Baseline Attention
Highest Auditory Task
Measure
FSAQ
-0.06
AAQ
-0.12
VAQ
-0.10
FSRQ
0.20
VPQ
0.28
APQ
0.27
TMT
A
0.20
B
0.26
PASAT
2.4
0.48*
2.0
0.57*
Bells
Left
0.04
Centre
0.01
Right
0.04
*Correlation is significant at the 0.05 level
Highest Visual Task
-0.05
-0.08
-0.13
-0.02
-0.04
0.09
-0.15
-0.18
0.29
0.32
-0.13
0.10
-0.43*
283
Table E-3
Correlations between baseline neuropsychological measures and highest
and visual task reached
Baseline Measure
Highest Auditory Task
Stroop
Dot
0.27
Word
0.17
Colour
0.36
ROCF
Copy
0.14
SD
0.35
LD
0.43*
Recognition
0.14
VPA
Learning
0.14
Delayed
0.11
BNT
0.34
LM1
-0.03
LM11
0.06
COWA
0.14
CVLT
SD Free
0.03
LD Free
0.05
Recognition
-0.09
*Correlation is significant at the 0.05 level
Highest Visual Task
-0.01
-0.06
0.16
-0.12
0.09
0.10
0.09
0.09
0.11
0.25
0.10
0.06
0.17
-0.10
-0.09
0.07
Table E-4
Correlations between post-intervention attention measures and highest
auditory and visual task reached.
Post-intervention
Highest Auditory Task Highest Visual Task
Attention Measure
FSAQ
0.07
0.14
AAQ
-0.10
-0.01
VAQ
0.13
0.11
FSRQ
0.11
0.13
VPQ
0.05
-0.00
APQ
0.00
0.09
TMT
A
0.04
-0.05
B
0.13
-0.06
PASAT
2.4
0.21
0.17
2.0
0.10
0.14
Bells
Left
0.28
0.15
Centre
-0.02
-0.19
Right
-0.01
-0.26
284
Appendix F
Tables showing correlations between baseline and post-intervention
measures with total hours of APT completed
Table F-1
Correlations between demographic measures and total
hours of APT completed
Baseline Demographic
Total Hours
Age
0.27
Gender
-0.26
Education
-0.07
Time since stroke
0.02
MMSE
-0.40*
Barthel Index
-0.29
*Correlation is significant at the 0.05 level
Table F-2
Correlations between baseline attention measures and
total hours of APT completed
Baseline Attention
Total Hours
Measure
IVA-CPT
FSAQ
-0.11
AAQ
0.01
VAQ
-0.22
FSRQ
0.19
VPQ
0.23
APQ
0.41*
TMT
A
-0.16
B
0.13
PASAT
2.4
0.05
2.0
0.07
Bells
Left
-0.05
Centre
0.07
Right
-0.05
*Correlation is significant at the 0.05 level
285
Table F-3
Correlations between baseline neuropsychological
measures and total hours of APT completed
Baseline Measure
Stroop
Dot
Word
Colour
ROCF
Copy
SD
LD
Recognition
VPA
Learning
Delayed
BNT
LM1
LM11
COWA
CVLT
SD Free
LD Free
Recognition
Total Hours
0.00
-0.03
-0.06
-0.03
0.05
0.06
-0.12
-0.09
-0.16
0.30
-0.08
0.02
-0.05
-0.08
0.01
-0.28
Table F-4
Correlations between post-intervention attention
measures and total hours of APT completed
Post-intervention
Total Hours
Attention Measure
IVA-CPT
FSAQ
-0.07
AAQ
-0.21
VAQ
-0.01
FSRQ
-0.08
VPQ
0.12
APQ
0.20
TMT
A
-0.10
B
-0.26
PASAT
2.4
-0.38
2.0
-0.40
Bells
Left
0.14
Centre
-0.07
Right
-0.07
SF-36
MCS
-0.03